Recon Skills is a pack of security-testing skills covering reconnaissance, web applications, APIs, authentication, vulnerability validation, cloud infrastructure, and reporting. Security professionals use it for authorized assessments of systems they own or have written permission to test. The catalogue entries are individual skills from the pack.
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 uphiago/recon-skills --skill cache-attackgit clone --depth 1 https://github.com/uphiago/recon-skillsWrote 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/uphiago/recon-skills/cache-attack)<a href="https://agentmods.dev/skills/uphiago/recon-skills/cache-attack"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/cache-attack/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/uphiago/recon-skills/cache-attack"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/cache-attack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 228 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Prompt Injection · line 252 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00018 | $0.03062 |
| Opus 5.5 | $0.00007 | $0.01225 |
| Sonnet 5.5 | $0.00004 | $0.00612 |
| Haiku 4.5 | $0.00002 | $0.00306 |
Grade A, and why
cache-attack 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
compatibility: Requires curl How it starts
The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cache Attack Skill
Web Cache Poisoning (WCP) and Web Cache Deception (WCD) methodology. WCP poisons cached pages with malicious content served to other users. WCD tricks the cache into storing sensitive pages that the attacker can then read. Both techniques exploit CDN and reverse-proxy caching behavior on CloudFront, Cloudflare, Fastly, Varnish, and Nginx.
When to Use
- Target uses a CDN (CloudFront, Cloudflare, Fastly) or reverse proxy (Varnish, Nginx cache).
- Headers show
X-Cache,Age,cf-cache-status, orX-Cache-Hits. - After surface recon finds no direct vulnerabilities — pivot to infrastructure layer.
- Target allows file extension manipulation in URL paths (.css, .json, .js).
Prerequisites
terminalwith curl.- Cache buster parameter for safe testing (
?cb=RANDOM). - Patience: cache poisoning requires precise timing and may need multiple attempts.
How to Run
# Phase 1: Detect cache
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/" | grep -iE "age|x-cache|cf-cache-status|via|server"
# Phase 2: Test cache storage (two identical requests)
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/?cb=TEST1" | grep -iE "x-cache|cf-cache-status"
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/?cb=TEST1" | grep -iE "x-cache|cf-cache-status"
# Second response should show HIT if caching works
# Phase 3: Test unkeyed header reflection
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/" -H "X-Forwarded-Host: evil.com" | grep -i "location\|evil.com"
Quick Reference
Web Cache Poisoning (WCP) — attacker poisons cache for victims
| Reflection Location | Impact | Severity |
|---|---|---|
<link rel="canonical"> |
SEO poisoning | Medium |
<script src="..."> |
XSS (stored in cache) | Critical |
<meta property="og:url"> |
Phishing (link preview) | High |
Location: header |
Mass open redirect | High |
<form action="..."> |
Credential theft | High |
<link rel="stylesheet"> |
CSS injection | Medium |
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 · 281 lines · 18 tokens per session scan A 769b8192c891
cache-attack is a skill published in the GitHub repository uphiago/recon-skills (1,308 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 3,062 once invoked, about $0.0001 per session on Opus 5.5. 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 skills, from other repositories
detecting-compromised-cloud-credentials
Detecting compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.
implementing-aws-config-rules-for-compliance
Implementing AWS Config rules for continuous compliance monitoring of AWS resources, deploying managed and custom rules aligned to CIS and PCI DSS frameworks, configuring automatic remediation with SSM Automation, and aggregating compliance data across accounts.
implementing-cloud-dlp-for-data-protection
Implementing Cloud Data Loss Prevention (DLP) using Amazon Macie, Azure Information Protection, and Google Cloud DLP API to discover, classify, and protect sensitive data across cloud storage, databases, and data pipelines.
implementing-cloud-trail-log-analysis
Implementing AWS CloudTrail log analysis for security monitoring, threat detection, and forensic investigation using Athena, CloudWatch Logs Insights, and SIEM integration to identify unauthorized access, privilege escalation, and suspicious API activity.
implementing-zero-trust-network-access
Implementing Zero Trust Network Access (ZTNA) in cloud environments by configuring identity-aware proxies, micro-segmentation, continuous verification with conditional access policies, and replacing traditional VPN-based access with BeyondCorp-style architectures across AWS, Azure, and GCP.
securing-api-gateway-with-aws-waf
Securing API Gateway endpoints with AWS WAF by configuring managed rule groups for OWASP Top 10 protection, creating custom rate limiting rules, implementing bot control, setting up IP reputation filtering, and monitoring WAF metrics for security effectiveness.