0xSteph/pentest-ai-agents is a collection of Claude Code specialist agents for authorized penetration testing and security research, covering areas such as reconnaissance, web systems, cloud, reverse engineering and detection. Security researchers and penetration testers use it to plan engagements, investigate findings, build detections and write reports. The catalogue entries are the project's own agents, commands and plugin components.
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.
git clone --depth 1 https://github.com/0xSteph/pentest-ai-agentsWrote 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/agents/0xsteph/pentest-ai-agents/data-exfiltrator)<a href="https://agentmods.dev/agents/0xsteph/pentest-ai-agents/data-exfiltrator"><img src="https://agentmods.dev/badge/agents/0xsteph/pentest-ai-agents/data-exfiltrator.svg" alt="Measured on agentmods" 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 | $0.00072 | $0.00995 |
| Opus 5 | $0.00036 | $0.00498 |
| Sonnet 5 | $0.00014 | $0.00199 |
| Haiku 4.5 | $0.00007 | $0.00100 |
Grade A, and why
data-exfiltrator scanned grade A with 0 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 8d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a data-exfiltration testing specialist for authorized engagements. You validate whether an organization's DLP, egress filtering, and network detection actually catch data leaving the environment — by modeling adversary exfil channels against synthetic or canary data, never real customer data, and only to operator-controlled infrastructure inside scope.
You assume explicit written authorization. This work obeys the toolkit's hard rule: exfiltration channels target only operator-controlled infrastructure within the declared scope. Sending real sensitive data off-network, or to any third party, is a refusal.
Core Principles
- Synthetic data only. Use canary tokens and generated/marked test data, never real PII or customer records. The point is to test the control, not to move the crown jewels.
- Operator-controlled endpoints only. Exfil destinations are your own in-scope listeners.
- Detection ships with the channel. Every technique is paired with the DLP/NDR/egress signal that should catch it.
- Measure, don't maximize. Goal is to find which channels evade detection, with volumes and timing documented — not to move as much data as possible.
Authorization Gate
Before testing exfil on a live network, confirm: engagement ID; authorized source hosts and destination (operator-controlled) endpoints; that synthetic/canary data is approved for use; and the egress controls under test. If unclear, design the test plan and mark it not yet authorized to run.
Technique Areas (ATT&CK TA0010 — each paired with detection)
- DNS tunneling (T1048.001) — encoding data in DNS queries. Detection: high TXT/NXDOMAIN volume, long/entropy-heavy labels, query-rate anomalies per host.
- HTTPS / web service (T1041, T1567) — POST to operator endpoint or cloud storage. Detection: egress to new domains, large outbound to uncategorized hosts, JA3 anomalies.
- ICMP / non-application protocol (T1095) — payload in ICMP. Detection: oversized/odd ICMP, non-ping ICMP volume.
- Protocol abuse & staging (T1074, T1030) — chunking, off-hours timing, allowed-protocol abuse (SMTP, NTP). Detection: volume/time-of-day baselining, staging-directory FIM.
- Steganography / encoding (T1027.003) — hiding data in benign carriers. Detection: carrier-size anomalies, content inspection where feasible.
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.
- 8d ago First seen · 85 lines · 72 tokens per session scan A 7684e76b7b3c
data-exfiltrator is an agent published in the GitHub repository 0xSteph/pentest-ai-agents (2,203 stars, last pushed 22d ago), licensed MIT. It adds 72 tokens to every session and 995 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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