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 gitlab-public-recongit 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/gitlab-public-recon)<a href="https://agentmods.dev/skills/uphiago/recon-skills/gitlab-public-recon"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/gitlab-public-recon/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/gitlab-public-recon"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/gitlab-public-recon.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 12 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 Supply Chain · line 80 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 84 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 130 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Supply Chain · line 135 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Privilege Escalation · line 140 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 167 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 140 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 140 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 143 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 144 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 155 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 153 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00019 | $0.02742 |
| Opus 5 | $0.00010 | $0.01371 |
| Sonnet 5 | $0.00004 | $0.00548 |
| Haiku 4.5 | $0.00002 | $0.00274 |
Grade C, and why
gitlab-public-recon scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
API_VER=$(curl -sk --max-time 5 --connect-timeout 5 "https://$TARGET/api/v4/version" 2>/dev/null | python3 -c "import sys,json; d=json.load(sys.stdin); print(f'{d.get(\"version\",\"?\")} rev {d.get(\"revision\",\"?\")[:8 Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
compatibility: Requires curl, nmap, python3, masscan, subfinder, httpx, nuclei How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitLab Public Recon Skill
Enumerate publicly accessible GitLab repositories to extract source code, credentials, internal IPs, CI/CD tokens, deployment configurations, and environment files. GitLab instances with registration enabled or public visibility expose the entire development infrastructure. Confirmed on gov-finance-portal (3 public repos, 461K CPFs, internal IP 10.11.82.75, CI/CD tokens), dev-agency (GitLab with SSL private keys), and fitness-chain (Firebase SA keys in repos).
When to Use
- Target has a
gitlab.subdomain or self-hosted GitLab instance. - crt.sh reveals
gitlab.target.comin certificates. - After
subdomain-enumerationdiscovers GitLab hosts. - After
js-secrets-extractionfinds GitLab CI/CD references. - Target is a government agency or large enterprise (common self-hosted GitLab users).
Prerequisites
terminalwith curl, python3, jq.- GitLab URL (e.g.,
https://gitlab.target.com). - GitLab API is accessible without authentication for public resources.
How to Run
# List public projects
curl --max-time 30 --connect-timeout 10 -sk "https://gitlab.TARGET.com/api/v4/projects?visibility=public&per_page=100" | jq '.[].path_with_namespace'
# Read a file from a public repo
curl --max-time 30 --connect-timeout 10 -sk "https://gitlab.TARGET.com/api/v4/projects/GROUP%2FPROJECT/repository/files/PATH/raw?ref=main"
Quick Reference
| API Endpoint | What It Returns | Risk |
|---|---|---|
/api/v4/projects?visibility=public |
All public projects | Info |
/api/v4/projects/:id/repository/tree |
Directory listing | High |
/api/v4/projects/:id/repository/files/:path/raw?ref=:branch |
Raw file content | Critical |
/api/v4/projects/:id/repository/commits |
Commit history with authors | Medium |
/api/v4/projects/:id/variables |
CI/CD variables (admin only) | Critical |
/api/v4/projects/:id/jobs |
CI/CD job history | Medium |
/users/sign_up |
Open registration | Critical |
/explore |
Public project explorer | Info |
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.
- 10d ago First seen · 237 lines · 19 tokens per session scan C 27db6859e103
gitlab-public-recon is a skill published in the GitHub repository uphiago/recon-skills (1,251 stars, last pushed 8d ago), licensed MIT. It adds 19 tokens to every session and 2,742 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, 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
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.
auditing-gcp-iam-permissions
Auditing Google Cloud Platform IAM permissions to identify overly permissive bindings, primitive role usage, service account key proliferation, and cross-project access risks using gcloud CLI, Policy Analyzer, and IAM Recommender.
auditing-terraform-infrastructure-for-security
Auditing Terraform infrastructure-as-code for security misconfigurations using Checkov, tfsec, Terrascan, and OPA/Rego policies to detect overly permissive IAM policies, public resource exposure, missing encryption, and insecure defaults before cloud deployment.
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.
detecting-misconfigured-azure-storage
Detecting misconfigured Azure Storage accounts including publicly accessible blob containers, missing encryption settings, overly permissive SAS tokens, disabled logging, and network access violations using Azure CLI, PowerShell, and Microsoft Defender for Storage.
detecting-s3-data-exfiltration-attempts
Detecting data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty findings, Amazon Macie alerts, and S3 access patterns to identify unauthorized bulk downloads and cross-account data transfers.