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https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
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mukul975
8cae0648ec
Demand-driven expansion targeting the fastest-growing 2025-2026 threat and
skills categories (ISC2/WEF/CrowdStrike/Mandiant signals):
- AI Security (NEW domain, 12 skills): LLM red-teaming with garak/PyRIT,
prompt injection (direct/indirect/RAG), MCP tool-poisoning, agentic tool
invocation, guardrails, model/data poisoning, system-prompt leakage,
embedding/vector weaknesses, model extraction, continuous red-teaming
- Supply Chain Security (NEW domain, 5 skills): SBOMs, dependency confusion,
malicious-npm triage, typosquatting, SLSA/Sigstore provenance
- Hardware & Firmware Security (NEW domain, 4 skills): CHIPSEC/UEFI audit,
Secure Boot bypass, TPM measured-boot attestation, ESP bootkit hunting
- Identity (10): Entra ID/ROADtools, GraphRunner, AADInternals, ADCS/Certipy,
shadow credentials, coercion, BloodHound CE, device-code phishing, SSO abuse
- Cloud-native (8): Stratus, Pacu, CloudFox, container escape, K8s RBAC,
Falco, Trivy, kube-bench
- Offensive C2 (6): Sliver, Havoc, NetExec, DPAPI, NTLM relay ESC8, redirectors
- DFIR (6): Hayabusa, Chainsaw, KAPE, Velociraptor, EZ Tools, Plaso
- Backfill (4): OpenCTI, MISP, honeytokens, post-quantum crypto migration
Each skill follows the repo taxonomy (SKILL.md + references/{standards,api-reference}.md
+ scripts/agent.py + LICENSE), with researched real tool commands (no placeholders),
complete frontmatter, and ATT&CK/ATLAS + NIST CSF mappings. Updates README domain
table, skill count, and index.json.
2.2 KiB
2.2 KiB
Plaso / log2timeline Command Reference
Plaso ships four CLI tools. Run them directly or via the Docker image
(log2timeline/plaso).
log2timeline.py (extraction)
| Flag | Purpose |
|---|---|
--storage-file <file> |
Output .plaso storage file |
<source> |
Source: .E01, raw image, mount point, directory, device |
--parsers <list> |
Restrict parsers (presets win7, webhist, etc.; !name excludes) |
--partitions <spec> |
Select partitions (e.g. all) |
--vss-stores <spec> |
Process Volume Shadow Copies |
--hashers <list> |
Compute file hashes (e.g. sha256) |
-z <tz> |
Source timezone |
--workers <n> |
Number of extraction workers |
log2timeline.py --storage-file timeline.plaso /cases/image.E01
log2timeline.py --parsers "win7,!filestat" --storage-file timeline.plaso /cases/image.E01
pinfo.py (inspect)
pinfo.py timeline.plaso # summary
pinfo.py -v timeline.plaso # verbose
psort.py (post-process / export)
| Flag | Purpose |
|---|---|
-o <module> |
Output module: l2tcsv, json_line, dynamic, elastic, timesketch |
-w <file> |
Write output to file |
--output-time-zone <tz> |
Normalize output timezone (e.g. UTC) |
<storage> |
The .plaso file |
"<filter>" |
Event filter expression (trailing argument) |
psort.py --output-time-zone 'UTC' -o l2tcsv -w supertimeline.csv timeline.plaso \
"date > datetime('2026-01-01T00:00:00') AND date < datetime('2026-01-27T00:00:00')"
psort.py --output-time-zone 'UTC' -o json_line -w supertimeline.jsonl timeline.plaso
psteal.py (extract + export wrapper)
psteal.py --source /cases/image.E01 -o l2tcsv -w supertimeline.csv
Common event filter fields
| Field | Example |
|---|---|
date |
date > datetime('2026-01-01T00:00:00') |
data_type |
data_type == 'windows:evtx:record' |
parser |
parser contains 'winreg' |
timestamp_desc |
timestamp_desc contains 'Creation' |
Timesketch import
timesketch_importer \
--host http://127.0.0.1:5000 \
--username admin \
--timeline_name "host01" \
--sketch_id 1 \
timeline.plaso
timesketch_importer accepts .plaso, .csv, and .jsonl inputs.