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 hunt-idorgit 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/hunt-idor)<a href="https://agentmods.dev/skills/uphiago/recon-skills/hunt-idor"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-idor/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/hunt-idor"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/hunt-idor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 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 191 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.
- medium Excessive Agency · line 239 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 372 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 135 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00030 | $0.05818 |
| Opus 5 | $0.00015 | $0.02909 |
| Sonnet 5 | $0.00006 | $0.01164 |
| Haiku 4.5 | $0.00003 | $0.00582 |
Grade A, and why
hunt-idor 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.
axios.get('/invoices/' + invoiceId) How it starts
The opening of the file, as written. The whole thing — 436 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
Use when the target has any endpoint that references user-owned resources by ID — API paths with user/order/invoice/message IDs, GraphQL queries with id arguments, file download endpoints, or any multi-tenant SaaS feature. IDOR is one of the most common and highest-paying vulnerabilities because it directly exposes other users' data without authentication bypass. Every feature that displays or acts on a resource by identifier is a candidate. Highest-value targets: financial documents/billing APIs, private repositories, user messages, account management endpoints, and cross-tenant business/org administration features.
Crown Jewel Targets
Why IDOR pays big:
- Direct access to other users' data without authentication bypass — clear, demonstrable impact
- Chains easily with privilege escalation, financial fraud, and account takeover
- Affects virtually every application with user-owned resources
Highest-value asset types (by payout potential):
| Asset Type | Why It Pays |
|---|---|
| Financial documents / billing APIs | PII + financial data exposure (Shopify, Uber, PayPal) |
| Private repositories / source code | IP theft, critical data loss (GitHub) |
| User messages / DMs | Privacy violation at scale (Reddit) |
| Account management endpoints | User addition, deletion, privilege escalation (PayPal, Mozilla) |
| Business/org administration | Cross-tenant escalation, employee PII (Uber) |
| Content moderation/admin actions | Operational sabotage (Reddit mod logs) |
Programs that pay most for IDOR:
- Platforms with multi-tenancy (SaaS, B2Btools)
- Fintech and payment processors
- Social platforms with private content
- Developertools with org/repo isolation
Attack Surface Signals
URL patterns that scream IDOR:
/api/v1/users/{id}/
/api/v*/orders/{order_id}
/invoices/download?id=
/reports/{uuid}/
/messages/{thread_id}
/admin/orgs/{org_id}/members
/migration/{migration_id}/files
/graphql (query params with IDs)
/api/business/{business_id}/
/vouchers/{voucher_id}/policy
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 · 436 lines · 30 tokens per session scan A 192fc09bd96e
hunt-idor is a skill published in the GitHub repository uphiago/recon-skills (1,254 stars, last pushed 10d ago), licensed MIT. It adds 30 tokens to every session and 5,818 once invoked, about $0.0002 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
detecting-api-enumeration-attacks
Detect and prevent API enumeration attacks including BOLA and IDOR exploitation by monitoring sequential identifier access patterns and authorization failures.
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.