Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification.
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Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
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epx add mukul975/Anthropic-Cybersecurity-Skills/detecting-sql-injection-via-waf-logsCompatible with
Supported agents
| name | detecting-sql-injection-via-waf-logs |
| description | Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification. |
| domain | cybersecurity |
| subdomain | security-operations |
| tags | - detecting - sql - injection - via |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - DE.CM-01 - RS.MA-01 - GV.OV-01 - DE.AE-02 |
pip install requestspython scripts/agent.py --log-file /var/log/modsec_audit.log --format modsecurity --output sqli_report.json
Rule 942100 triggered: SQL Injection Attack Detected via libinjection
URI: /api/users?id=1' UNION SELECT username,password FROM users--
Source IP: 203.0.113.42 (47 requests in 5 minutes)
Classification: UNION-based SQLi campaign
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondetecting-sql-injection-via-waf-logsExecute the skills CLI command in your project's root directory to begin installation:
epx add mukul975/Anthropic-Cybersecurity-Skills/detecting-sql-injection-via-waf-logsFetches detecting-sql-injection-via-waf-logs from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/detecting-sql-injection-via-waf-logs
Restart Cursor to activate detecting-sql-injection-via-waf-logs. Access via /detecting-sql-injection-via-waf-logsin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
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✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
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Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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detecting-sql-injection-via-waf-logs reduced setup friction for our internal harness; good balance of opinion and flexibility.
detecting-sql-injection-via-waf-logs is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
detecting-sql-injection-via-waf-logs reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added detecting-sql-injection-via-waf-logs from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for detecting-sql-injection-via-waf-logs matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend detecting-sql-injection-via-waf-logs for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in detecting-sql-injection-via-waf-logs — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: detecting-sql-injection-via-waf-logs is the kind of skill you can hand to a new teammate without a long onboarding doc.
Keeps context tight: detecting-sql-injection-via-waf-logs is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend detecting-sql-injection-via-waf-logs for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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