Atlas / MCP servers / cybersecurityup / Offensive AI

Offensive AISAFE

mcp/cybersecurityup/offensive-ai
Verdict
SAFE
Grade
B
Trust score
89 /100
Exposed tools
16 8r · 8w · 0d
Transport
—
License
—
Stars
27
01

Overview

From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.

🔮 Future Work Using MCP and AI

  1. Autonomous Red Team Agents

Build LLM-driven agents that autonomously conduct reconnaissance, payload generation, exploitation and reporting, all orchestrated via MCP tools.

  1. AI-Powered SOC Analyst

Integrate Wazuh + Suricata + Zeek logs and use MCP to let Claude analyze incidents, detect lateral movement, and recommend response actions in real-time.

  1. Malware Dev Studio (LLM + MCP)

Use Claude + MCP to automate shellcode generation, obfuscation, sandbox evasion, and EDR bypass strategies through tools like Capstone, Donut, and Sliver.

  1. Threat Hunting Automation

Develop proactive AI workflows that analyze logs, correlate indicators, and hunt based on threat intelligence feeds via MCP resources and tools.

  1. Agent-Based Purple Team Simulator

Combine MCP with ATT&CK simulations, where Claude orchestrates both Red and Blue side techniques (Atomic Red Team, Caldera, Sigma/YARA rule generation).

  1. CI/CD + DevSecOps Integration

Use MCP to review code pushed to GitHub, scan secrets, trigger security tools (Trufflehog, Gitleaks), and send secure alerts or PR recommendations.

  1. Auto Incident Report Generator

Claude consumes logs and tool outputs via MCP and generates full incident reports (including diagrams and mitigations) in Markdown or PDF formats.

  1. Cybersecurity Tutor / Trainer Mode

Claude explains what each tool does, simulates attacks in safe lab environments, and evaluates user responses via MCP simulation tools.

🔗 Installation & Integration Links

✅ Install MCP CLI and SDK (Python)

pip install modelcontextprotocol

Docs: 🔗 https://modelcontextprotocol.io/quickstart/server GitHub: 🔗 https://github.com/jlowin/fastmcp

🧠 Claude Desktop Configuration (Mac, Linux, Windows)

  1. Install Claude for Desktop

🔗 https://www.anthropic.com/index/claude-desktop

  1. Edit config file:

macO

Read from source at commit 55b65f1a4c25OBSERVED · 2026-10-09
Advertisement
02

Exposed tools (16)

8 read · 8 write · 0 destructive.

ToolRiskDescription
analyze_rulesetread
block_ip_with_firewallread
count_high_severity_alertsread
extract_shellcoderead
generate_donutread
generate_msfvenomread
generate_sliverread
run_assetfinderwrite
run_digwrite
run_dnsreconwrite
run_sslscanwrite
run_subfinderwrite
run_tlsxwrite
run_whoiswrite
save_source_and_compilewrite
tail_wazuh_alertsread
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
declared (4 observation(s))
Dependencies
pinned
Secrets in source
none-found

Findings (1)

LOWInventory / provenance · inv.no_license · CWE-1104
Why it matters. no LICENSE file and no repo licence
Fix. add a licence

Gates applied: no_behavioural_pass, no_license.

Audited 2026-10-09 · audit v0.4.1 · source sha 55b65f1a4c25full audit observations/trust-audit/mcp-server/cybersecurityup__offensive-ai.json · Report an issue / request a re-scan
04

Audit history

Every audit this server has had. A grade with a past is a grade somebody is still checking.

DateSourceVerdictGradeScoreChange
2026-10-0955b65f1a4c25SAFEB89first audit
05

Questions

What tools does Offensive AI expose?

16 in total: 8 read-only, 8 that write, and 0 that can delete or overwrite. Every one is listed on this page with its risk.

Is Offensive AI safe to connect to an agent?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean server reads B.

What credentials does Offensive AI need?

No credential environment variables were found in its source, so it appears to need none.

How current is this page?

The grade is for one exact copy of the source (55b65f1a4c25), read on 2026-10-09. The repository is watched and re-audited when it changes.

Advertisement