Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/akashrpatil/awesome-offensive-security-skillsnpx agentmods add skills/akashrpatil/awesome-offensive-security-skills/zero-logon-exploitationWrote 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/akashrpatil/awesome-offensive-security-skills/zero-logon-exploitation)<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/zero-logon-exploitation"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/zero-logon-exploitation/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/akashrpatil/awesome-offensive-security-skills/zero-logon-exploitation"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/zero-logon-exploitation.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 | $0.00070 | $0.01544 |
| Opus 5 | $0.00035 | $0.00772 |
| Sonnet 5 | $0.00014 | $0.00309 |
| Haiku 4.5 | $0.00007 | $0.00154 |
Grade A, and why
zero-logon-exploitation 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 7d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ZeroLogon Exploitation (CVE-2020-1472)
When to Use
- EXTREME WARNING: Utilizing this exploit in a production environment will inherently break the Domain Controller's communication with the rest of the domain until its password is reconstructed properly from the registry. Only utilize this on authorized Red Team engagements against non-patched legacy systems where the risk is pre-approved.
- When you have network line-of-sight to the Domain Controller and need a direct, unauthenticated path to Domain Administrator capabilities.
- To demonstrate the catastrophic impact of failing to patch critical cryptography flaws in core identity infrastructure.
Prerequisites
- Authorized scope and rules of engagement for the target environment
- Appropriate tools installed on the attack/analysis platform
- Understanding of the target technology stack and architecture
- Documentation template ready for findings and evidence capture
Workflow
Phase 1: Understanding the Flaw (The Concept)
# Concept: The Netlogon protocol uses a flawed cryptographic implementation for authentication
# specifically the AES-CFB8 encryption scheme.
# The Vulnerability ```
### Phase 2: Detecting Vulnerability
```bash
# Before launching the attack, definitively verify if the DC is unpatched without breaking it.
# We utilize the standard Python tester script (widely available on GitHub from Secura).
python3 zerologon_tester.py DC-NAME 192.168.1.10
# Expected Vulnerable Output:
# Performing authentication attempts...
# Success! DC can be fully compromised by a Zerologon attack.
# Expected Patched Output:
# Attack failed. Target is probably patched.
Phase 3: Exploitation (The Zeroing)
# CONCEPT: The exploit We use the full exploit script (e.g., cve-2020-1472-exploit.py)
python3 cve-2020-1472-exploit.py DC-NAME 192.168.1.10
# Output Result: Success! DC machine password has been set to empty string.
Phase 4: Dumping the Hashes (secretsdump)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 157 lines · 70 tokens per session scan A accb493f73b1
zero-logon-exploitation is a skill published in the GitHub repository akashrpatil/awesome-offensive-security-skills (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 70 tokens to every session and 1,544 once invoked, about $0.0003 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 2026-09-03.
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