ctf-forensics▌
ljagiello/ctf-skills · updated Apr 8, 2026
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Comprehensive digital forensics and signal analysis toolkit for CTF challenges across disk, memory, network, and steganography domains.
- ›Covers 15+ forensics categories: disk/memory imaging (Volatility, VM forensics, coredumps), Windows registry/event logs/SAM, Linux logs/Docker, network analysis (PCAP, TLS decryption, SMB, NTLMv2), and browser artifact extraction
- ›Includes advanced steganography techniques: image LSB/bitplane extraction, PDF multi-layer stego, audio DTMF/FFT/SSTV, SVG ke
CTF Forensics & Blockchain
Quick reference for forensics CTF challenges. Each technique has a one-liner here; see supporting files for full details.
Prerequisites
Python packages (all platforms):
pip install volatility3 Pillow numpy matplotlib
Linux (apt):
apt install binwalk foremost libimage-exiftool-perl tshark sleuthkit \
ffmpeg steghide testdisk john pcapfix
macOS (Homebrew):
brew install binwalk exiftool wireshark sleuthkit ffmpeg \
testdisk john-jumbo
Ruby gems (all platforms):
gem install zsteg
Additional Resources
- 3d-printing.md - 3D printing forensics (PrusaSlicer binary G-code, QOIF, heatshrink)
- windows.md - Windows forensics (registry, SAM, event logs, recycle bin, NTFS alternate data streams, USN journal, PowerShell history, Defender MPLog, WMI persistence, Amcache)
- network.md - Network forensics basics (tcpdump, TLS/SSL keylog decryption, TLS master key extraction from coredump, Wireshark, PCAP, port scanning, SMB3 decryption, 5G/NR protocols, WordPress recon, credentials, USB HID steno, BCD encoding, HTTP file upload exfiltration, split archive reassembly via timestamp ordering)
- network-advanced.md - Advanced network forensics (packet interval timing encoding, USB HID mouse/pen drawing recovery, NTLMv2 hash cracking, TCP flag covert channel, DNS last-byte steganography, DNS trailing byte binary encoding, multi-layer PCAP with XOR + ZIP and mDNS key, Brotli decompression bomb seam analysis, SMB RID recycling via LSARPC, Timeroasting MS-SNTP hash extraction)
- disk-and-memory.md - Core disk/memory forensics (Volatility, disk mounting/carving, VM/OVA/VMDK, VMware snapshots, GIMP raw memory dump visual inspection, coredumps, Windows KAPE triage, PowerShell ransomware, Android forensics, Docker container forensics, cloud storage forensics, BSON reconstruction, TrueCrypt/VeraCrypt mounting)
- disk-advanced.md - Advanced disk and memory techniques (deleted partitions, ZFS forensics, GPT GUID encoding, VMDK sparse parsing, memory dump string carving, ransomware key recovery, WordPerfect macro XOR, minidump ISO 9660 recovery, APFS snapshot recovery, RAID 5 XOR recovery, HFS+ resource fork recovery, Kyoto Cabinet hash DB forensics, SQLite edit history reconstruction)
- disk-recovery.md - Disk recovery and extraction patterns (LUKS master key recovery, PRNG timestamp seed brute-force, VBA macro binary recovery, FemtoZip decompression, XFS filesystem reconstruction, tar duplicate entry extraction, nested matryoshka filesystem extraction, anti-carving via null byte interleaving, BTRFS subvolume/snapshot recovery, FAT16 free space data recovery, FAT16 deleted file recovery via Sleuth Kit fls/icat, ext2 orphaned inode recovery via fsck, corrupted ZIP header repair)
- steganography.md - General steganography (binary border stego, PDF multi-layer stego, SVG keyframes, PNG reorder, file overlays, GIF frame diff Morse code, GZSteg + spammimic, spreadsheet frequency recovery, Kitty terminal graphics protocol decoding, ANSI escape sequence steganography, autostereogram solving, two-layer byte+line interleaving, multi-stream video container stego, progressive PNG layered XOR decryption, QR code reconstruction from curved reflection)
- stego-image.md - Image-specific steganography (JPEG unused DQT table LSB, BMP bitplane QR extraction, image puzzle reassembly, F5 JPEG DCT ratio detection, PNG unused palette entry stego, QR code tile reconstruction, seed-based pixel permutation + multi-bitplane QR, JPEG thumbnail pixel-to-text mapping, conditional LSB with pixel filtering, JPEG slack space, nearest-neighbor interpolation stego, RGB parity steganography)
- stego-advanced.md - Advanced steganography part 1: audio and signal techniques (FFT frequency domain, DTMF audio, SSTV+LSB, DotCode barcode, custom frequency dual-tone keypad, multi-track audio differential subtraction, cross-channel multi-bit LSB, audio FFT musical notes, audio metadata octal encoding, nested tar whitespace encoding, DeepSound audio stego with password cracking, audio waveform binary encoding, audio spectrogram hidden QR)
- stego-advanced-2.md - Advanced steganography part 2: video, image transform, and format-specific techniques (video frame accumulation, reversed audio, video frame averaging, JPEG XL TOC permutation steganography, Arnold's Cat Map descrambling, high-resolution SSTV custom FM demodulation, MJPEG FFD9 trailing byte stego, EXIF zlib + Stegano pixel patterns, PDF xref covert channel, ANSI escape code stego, pixel-wise ECB deduplication)
- linux-forensics.md - Linux/app forensics (log analysis, Docker image forensics, attack chains, browser credentials, Firefox history, TFTP, TLS weak RSA, USB audio, Git directory recovery, KeePass v4 cracking, Git reflog/fsck squash recovery, browser artifact analysis (Chrome/Chromium/Firefox history, cookies, downloads, local storage, session restore), corrupted git blob repair via byte brute-force, VBA macro Excel cell data to ELF binary extraction, Python in-memory source recovery via pyrasite)
- signals-and-hardware.md - Hardware signal decoding with decode code (VGA frame parsing, HDMI TMDS symbol decode, DisplayPort 8b/10b + LFSR descrambler), Voyager Golden Record audio, Saleae Logic 2 UART decode, Flipper Zero .sub files, side-channel power analysis (DPA), keyboard acoustic side-channel, CD audio disc image steganography (CIRC de-interleaving + spiral rendering), caps-lock LED Morse code from video, Linux input_event keylogger dump parsing, serial UART from WAV audio, USB MIDI Launchpad grid reconstruction
When to Pivot
- If you recover an encrypted blob and the hard part becomes RSA, AES, or lattice work, switch to
/ctf-crypto. - If the evidence really points to malware staging, beacon config extraction, or packed samples, switch to
/ctf-malware. - If the artifact is a web app backup or API dump and the remaining problem is application logic, switch to
/ctf-web. - If the forensic evidence is really an encoding puzzle, steganography trick, or esoteric format rather than true forensics, switch to
/ctf-misc. - If you need to trace infrastructure, attribute actors, or investigate public records from forensic findings, switch to
/ctf-osint. - If the recovered artifact is a compiled binary or firmware that needs disassembly and analysis, switch to
/ctf-reverse.
Quick Start Commands
# File analysis
file suspicious_file
exiftool suspicious_file # Metadata
binwalk suspicious_file # Embedded files
strings -n 8 suspicious_file
hexdump -C suspicious_file | head # Check magic bytes
# Disk forensics
sudo mount -o loop,ro image.dd /mnt/evidence
fls -r image.dd # List files
photorec image.dd # Carve deleted files
# Memory forensics (Volatility 3)
vol3 -f memory.dmp windows.info
vol3 -f memory.dmp windows.pslist
vol3 -f memory.dmp windows.filescan
See disk-and-memory.md for full Volatility plugin reference, VM forensics, and coredump analysis.
Log Analysis
grep -iE "(flag|part|piece|fragment)" server.log # Flag fragments
grep "FLAGPART" server.log | sed 's/.*FLAGPART: //' | uniq | tr -d '\n' # Reconstruct
sort logfile.log | uniq -c | sort -rn | head # Find anomalies
See linux-forensics.md for Linux attack chain analysis and Docker image forensics.
Windows Event Logs (.evtx)
Key Event IDs:
- 1001 - Bugcheck/reboot
- 1102 - Audit log cleared
- 4720 - User account created
- 4781 - Account renamed
RDP Session IDs (TerminalServices-LocalSessionManager):
- 21 - Session logon succeeded
- 24 - Session disconnected
- 1149 - RDP auth succeeded (RemoteConnectionManager, has source IP)
import Evtx.Evtx as evtx
with evtx.Evtx("Security.evtx") as log:
for record in log.records():
print(record.xml())
See windows.md for full event ID tables, registry analysis, SAM parsing, USN journal, and anti-forensics detection.
- NTFS Alternate Data Streams (ADS): Hidden data attached to files via named NTFS streams. Invisible to
dir/Explorer. Detect withfls -r image.dd | grep ":", extract withicat. See windows.md.
When Logs Are Cleared
If attacker cleared event logs, use these alternative sources:
- USN Journal ($J) - File operations timeline (MFT ref, timestamps, reasons)
- SAM registry - Account creation from key last_modified timestamps
- PowerShell history - ConsoleHost_history.txt (USN DATA_EXTEND = command timing)
- Defender MPLog - Separate log with threat detections and ASR events
- Prefetch - Program execution evidence
- User profile creation - First login time (profile dir in USN journal)
See windows.md for detailed parsing code and anti-forensics detection checklist.
Steganography
steghide extract -sf image.jpg
zsteg image.png # PNG/BMP analysis
stegsolve # Visual analysis
-
Binary border stego: Black/white pixels in 1px image border encode bits clockwise
-
FFT frequency domain: Image data hidden in 2D FFT magnitude spectrum; try
np.fft.fft2visualization -
DTMF audio: Phone tones encoding data; decode with
multimon-ng -a DTMF -
Multi-layer PDF: Check hidden comments, post-EOF data, XOR with keywords, ROT18 final layer
-
SSTV + LSB: SSTV signal may be red herring; check 2-bit LSB of audio samples with
stegolsb -
SVG keyframes: Animation
keyTimes/valuesattributes encode binary/Morse via fill color alternation -
PNG chunk reorder: Fix chunk order: IHDR → ancillary → IDAT (in order) → IEND
-
File overlays: Check after IEND for appended archives with overwritten magic bytes
-
APNG frame extraction: Animated PNG has multiple frames; extract with
apngdisor parsefdAT/fcTLchunks. See steganography.md. -
PNG height/CRC manipulation: Modify IHDR height field, brute-force until CRC matches to reveal hidden rows. See steganography.md.
-
Pixel coordinate chain stego: Linked-list traversal where R=data byte, G/B=next pixel coordinates. See stego-image.md.
-
AVI frame differential: XOR consecutive video frames to reveal hidden data in pixel differences. See stego-image.md.
-
Custom freq DTMF: Non-standard dual-tone frequencies; generate spectrogram first (
ffmpeg -i audio -lavfi showspectrumpic), map custom grid to keypad digits, decode variable-length ASCII -
JPEG DQT LSB: Unused quantization tables (ID 2, 3) carry LSB-encoded data; access via
Image.open().quantizationand extract bit 0 from each of 64 values -
Multi-track audio subtraction: Two nearly-identical audio tracks in MKV/video;
sox -m a0.wav "|sox a1.wav -p vol -1" diff.wavcancels shared content, flag appears in spectrogram of difference signal (5-12 kHz band) -
Packet interval timing: Identical packets with two distinct interval values (e.g., 10ms/100ms) encode binary; filter by interface, compute inter-packet deltas, threshold to bits
See steganography.md, stego-advanced.md, and stego-advanced-2.md for full code examples and decoding workflows.
PDF Analysis
exiftool document.pdf # Metadata (often hides flags!)
pdftotext document.pdf - # Extract text
strings document.pdf | grep -i flag
binwalk document.pdf # Embedded files
Advanced PDF stego (Nullcon 2026 rdctd): Six techniques -- invisible text separators, URI annotations with escaped braces, Wiener deconvolution on blurred images, vector rectangle QR codes, compressed object streams (mutool clean -d), document metadata fields.
See steganography.md for full PDF steganography techniques and code.
Disk / VM / Memory Forensics
# Disk images
sudo mount -o loop,ro image.dd /mnt/evidence
fls -r image.dd && photorec image.dd
# VM images (OVA/VMDK)
tar -xvf machine.ova
7z x disk.vmdk -oextracted "Windows/System32/config/SAM" -r
# Memory (Volatility 3)
vol3 -f memory.dmp windows.pslist
vol3 -f memory.dmp windows.cmdline
vol3 -f memory.dmp windows.netscan
vol3 -f memory.dmp windows.dumpfiles --physaddr <addr>
# String carving
strings -a -n 6 memdump.bin | grep -E "FLAG|SSH_CLIENT|SESSHow to use ctf-forensics on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add ctf-forensics
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches ctf-forensics from GitHub repository ljagiello/ctf-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate ctf-forensics. Access the skill through slash commands (e.g., /ctf-forensics) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★41 reviews- ★★★★★Ishan Rao· Dec 16, 2024
ctf-forensics has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aanya Menon· Dec 12, 2024
Registry listing for ctf-forensics matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Charlotte Flores· Dec 8, 2024
ctf-forensics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ganesh Mohane· Dec 4, 2024
ctf-forensics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Charlotte Lopez· Nov 27, 2024
ctf-forensics is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Nov 23, 2024
ctf-forensics is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Aarav Abebe· Nov 19, 2024
ctf-forensics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ishan Thomas· Nov 7, 2024
Useful defaults in ctf-forensics — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ishan Li· Oct 26, 2024
I recommend ctf-forensics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Tariq Reddy· Oct 18, 2024
Keeps context tight: ctf-forensics is the kind of skill you can hand to a new teammate without a long onboarding doc.
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