CapTipper - Malicious HTTP traffic explorer tool

CapTipper is a python tool to analyze, explore and revive HTTP malicious traffic.

CapTipper sets up a web server that acts exactly as the server in the PCAP file, and contains internal tools, with a powerful interactive console, for analysis and inspection of the hosts, objects and conversations found.

The tool provides the security researcher with easy access to the files and the understanding of the network flow,and is useful when trying to research exploits, pre-conditions, versions, obfuscations, plugins and shellcodes.

Feeding CapTipper with a drive-by traffic capture (e.g of an exploit kit) displays the user with the requests URI's that were sent and responses meta-data.

The user can at this point browse to http://127.0.0.1/[URI] and receive the response back to the browser.

In addition, an interactive shell is launched for deeper investigation using various commands such as: hosts, hexdump, info, ungzip, body, client, dump and more...

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DAMM - Differential Analysis of Malware in Memory

An open source memory analysis tool built on top of Volatility. It is meant as a proving ground for interesting new techniques to be made available to the community. These techniques are an attempt to speed up the investigation process through data reduction and codifying some expert knowledge.

Features

• ~30 Volatility plugins combined into ~20 DAMM plugins (e.g., pslist, psxview and other elements are combined into a 'processes' plugin)
• Can run multiple plugins in one invocation
• The option to store plugin results in SQLite databases for preservation or for "cached" analysis
• A filtering/type system that allows easily filtering on attributes like pids to see all information related to some process and exact or partial matching for strings, etc.
• The ability to show the differences between two databases of results for the same or similar machines and manipulate from the cmdline how the differencing operates
• The ability to warn on certain types of suspicious behavior
• Output for terminal, tsv or grepable

Usage

NOTE: Most DAMM output looks better piped through 'less -S' (upper 'S') as in: 
#python damm.py <some DAMM functionality> | less -S (for default output format)

python damm.py -h
usage: damm.py [-h] [-d DIR] [-p PLUGIN [PLUGIN ...]] [-f FILE] [-k KDBG]
               [--db DB] [--profile PROFILE] [--debug] [--info] [--tsv]
               [--grepable] [--filter FILTER] [--filtertype FILTERTYPE]
               [--diff BASELINE] [-u FIELD [FIELD ...]] [--warnings] [-q]

DAMM v1.0 Beta

optional arguments:
  -h, --help            show this help message and exit
  -d DIR                Path to additional plugin directory
  -p PLUGIN [PLUGIN ...]
                        Plugin(s) to run. For a list of options use --info
  -f FILE               Memory image file to run plugin on
  -k KDBG               KDBG address for the images (in hex)
  --db DB               SQLite db file, for efficient input/output
  --profile PROFILE     Volatility profile for the images (e.g. WinXPSP2x86)
  --debug               Print debugging statements
  --info                Print available volatility profiles, plugins
  --tsv                 Print screen formatted output.
  --grepable            Print in grepable text format
  --filter FILTER       Filter results on name:value pair, e.g., pid:42
  --filtertype FILTERTYPE
                        Filter match type; either "exact" or "partial",
                        defaults to partial
  --diff BASELINE       Diff the imageFile|db with this db file as a baseline
  -u FIELD [FIELD ...]  Use the specified fields to determine uniqueness of
                        memobjs when diffing
  --warnings            Look for suspicious objects.
  -q                    Query the supplied db (via --db).

Supported plugins

See #python damm.py --info

apihooks callbacks connections devicetree dlls evtlogs handles idt injections messagehooks mftentries modules mutants privileges processes services sids timers

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[Rekall] Memory Forensics Analysis Framework

The Rekall Framework is a completely open collection of tools, implemented in Python under the GNU General Public License, for the extraction of digital artifacts from volatile memory (RAM) samples. The extraction techniques are performed completely independent of the system being investigated but offer visibilty into the runtime state of the system. The framework is intended to introduce people to the techniques and complexities associated with extracting digital artifacts from volatile memory samples and provide a platform for further work into this exciting area of research.

Rekall should run on any platform that supports Python (http://www.python.org)

Rekall supports investigations of the following x86 bit memory images:

• Microsoft Windows XP Service Pack 2 and 3
• Microsoft Windows 7 Service Pack 0 and 1
• Linux Kernels 2.6.24 to 3.10.
• OSX 10.6-10.8.

Rekall also provides a complete memory sample acquisition capability for all major operating systems (see the tools directory).

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