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 report-writinggit 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/report-writing)<a href="https://agentmods.dev/skills/uphiago/recon-skills/report-writing"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/report-writing/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/report-writing"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/report-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00082 | $0.05936 |
| Opus 5 | $0.00041 | $0.02968 |
| Sonnet 5 | $0.00016 | $0.01187 |
| Haiku 4.5 | $0.00008 | $0.00594 |
Grade A, and why
report-writing 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 8d 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.
3. **The curl command or HTTP request block** (30 seconds) Copies of this mod
1 near-identical copy found in the catalogue:
- report-writing — 89% identical, 66 lines differ
How it starts
The opening of the file, as written. The whole thing — 630 lines — stays where its author put it; the contents beside it link to each section on GitHub.
REPORT WRITING
Impact-first. Human tone. No theoretical language. Triagers are people.
THE MOST IMPORTANT RULE
Never use "could potentially" or "could be used to" or "may allow". Either it does the thing or it doesn't. If you haven't proved it, don't claim it.
BAD: "This vulnerability could potentially allow an attacker to access user data."
GOOD: "An attacker can access any user's order history by changing the user_id
parameter to the target user's ID. I confirmed this using two test accounts:
[email protected] (ID 123) successfully retrieved [email protected] (ID 456)
orders, including their shipping address and payment method last 4 digits."
TITLE FORMULA
[Bug Class] in [Exact Endpoint/Feature] allows [attacker role] to [impact] [victim scope]
Good titles (specific, impact-first):
IDOR in /api/v2/invoices/{id} allows authenticated user to read any customer's invoice data
Missing auth on POST /api/admin/users allows unauthenticated attacker to create admin accounts
Stored XSS in profile bio field executes in admin panel — allows privilege escalation
SSRF via image import URL parameter reaches AWS EC2 metadata service
Race condition in coupon redemption allows same code to be used unlimited times
Bad titles (vague, useless to triager):
IDOR vulnerability found
Broken access control
XSS in user input
Security issue in API
Unauthorized access to user data
HACKERONE REPORT TEMPLATE
## Summary
[One paragraph: what the bug is, where it is, what an attacker can do. Be specific.
Include: endpoint, method, parameter, data exposed, required access level.]
Example: "The `/api/users/{user_id}/orders` endpoint does not verify that the
authenticated user owns the requested user_id. An attacker can enumerate any
user's order history, including PII (email, address, phone) and purchase history,
by incrementing the user_id parameter. No privileges beyond a standard free
account are required."
## Vulnerability Details
**Vulnerability Type:** IDOR / Broken Object Level Authorization
**CVSS 3.1 Score:** 6.5 (Medium) — AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
**Affected Endpoint:** GET /api/users/{user_id}/orders
## Steps to Reproduce
**Environment:**
- Attacker account: [email protected], user_id = 123
- Victim account: [email protected], user_id = 456
- Target: https://target.com
**Steps:**
1. Log in as [email protected], obtain Bearer token
2. Send the following request:
GET /api/users/456/orders HTTP/1.1 Host: target.com Authorization: Bearer ATTACKER_TOKEN_HERE
3. Observe response:
```json
{
"orders": [
{"id": 789, "items": [...], "email": "[email protected]", "address": "123 Main St..."}
]
}
The response contains victim's full order history and PII despite being requested by a different user.
Impact
An authenticated attacker can enumerate all user orders by iterating user_id values. This exposes: full name, email, shipping address, purchase history, and payment method (last 4). With ~100K users, this represents a mass PII breach affecting all registered users. Exploitation requires only a free account and takes minutes with a simple loop.
Recommended Fix
Add server-side ownership verification:
if order.user_id != current_user.id:
raise Forbidden()
Supporting Materials
[Screenshot showing attacker's session returning victim's order data] [Video walkthrough if available]
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.
- 8d ago First seen · 630 lines · 82 tokens per session scan A 5d39da76a95c
report-writing is a skill published in the GitHub repository uphiago/recon-skills (1,254 stars, last pushed 10d ago), licensed MIT. It adds 82 tokens to every session and 5,936 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 2026-09-03.
Other skills, from other repositories
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.
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.