detecting-sql-injection-via-waf-logs
by mukul975Analyze WAF and audit logs to detect SQL injection campaigns with detecting-sql-injection-via-waf-logs. Built for Security Audit and SOC workflows, it parses ModSecurity, AWS WAF, and Cloudflare events, classifies UNION SELECT, OR 1=1, SLEEP(), and BENCHMARK() patterns, correlates sources, and produces incident-oriented findings.
This skill scores 78/100, which means it is a solid listing candidate for directory users who need WAF-log-based SQL injection detection. The repository shows a real, executable workflow—not a placeholder—with a focused trigger, concrete log formats, detection patterns, and an analysis script, so users can judge fit before installing.
- Clear operational trigger: investigate SQL injection via ModSecurity, AWS WAF, or Cloudflare logs.
- Real workflow assets: SKILL.md plus a Python analysis script and API reference support actual execution.
- Good detection specificity: enumerates SQLi patterns and OWASP-style classifications for incident analysis.
- Install guidance is thin: SKILL.md references pip install requests but does not include a full run command or dependency list.
- Scope is security-ops specific: best for log analysis and threat hunting, not a general SQLi assistant or interactive testing tool.
Overview of detecting-sql-injection-via-waf-logs skill
What this skill does
The detecting-sql-injection-via-waf-logs skill helps you analyze WAF and audit logs to spot SQL injection activity faster and with less manual triage. It is built for Security Audit and SOC-style workflows where you need to turn noisy ModSecurity, AWS WAF, or Cloudflare events into a readable incident picture.
Who should install it
Install detecting-sql-injection-via-waf-logs if you investigate web attack traffic, tune detection rules, or validate monitoring coverage for SQLi patterns. It is a practical fit for analysts who already have logs and need a repeatable way to classify attacks, not a generic web security primer.
What makes it useful
The repo supports detection of common SQLi markers such as UNION SELECT, tautologies like OR 1=1, and time-based probes such as SLEEP() or BENCHMARK(). It also adds value by correlating attack sources, mapping findings to OWASP-style categories, and generating incident-oriented output instead of just flagging suspicious strings.
How to Use detecting-sql-injection-via-waf-logs skill
detecting-sql-injection-via-waf-logs install
Use the skill install command from the repository context, then open skills/detecting-sql-injection-via-waf-logs/SKILL.md first to confirm scope and prerequisites. If you are working in an agent environment, the key prompt is not just “analyze logs” but “analyze these WAF logs for SQLi indicators, summarize likely attack chains, and classify the findings for Security Audit.”
What input the skill needs
Give the skill raw or lightly normalized WAF data, plus the log source and time window. Strong inputs include sample fields like client IP, URI, request args, rule ID, action, and any blocked vs allowed status. If you have mixed sources, say which records came from ModSecurity audit logs versus JSON WAF events so the analysis can keep them separate.
Best workflow for usage
Start with a small representative log slice, then expand to a full incident range once the detection logic is behaving as expected. A good workflow is: parse the logs, identify candidate payloads, group repeated attempts by source and target, then review whether the pattern looks like probing, exploitation, or false positive noise. For this skill, that sequence matters more than a one-shot “find SQLi” request.
Files to read first
Read SKILL.md for the operating instructions, then references/api-reference.md for the rule and log-format map. If you need to understand implementation behavior or adapt the logic, inspect scripts/agent.py next. Those three files tell you what the detecting-sql-injection-via-waf-logs usage actually expects and where the detection boundaries are.
detecting-sql-injection-via-waf-logs skill FAQ
Is this only for ModSecurity?
No. The skill is designed for ModSecurity audit logs, AWS WAF JSON logs, and Cloudflare firewall-style events. If your platform stores different fields, the main requirement is that the relevant request, rule, and source data are still available for correlation.
Do I need to be a beginner in security operations?
No, but you do need basic log-reading comfort. The skill is most useful when you already know what WAF alerts, rule IDs, and blocked requests mean, because its value is in faster classification and evidence grouping rather than teaching the basics.
Why use this instead of a normal prompt?
A normal prompt can spot a suspicious string, but detecting-sql-injection-via-waf-logs skill gives you a structured workflow around payload detection, severity grouping, and incident reporting. That reduces guesswork when the logs are messy, multi-source, or full of repeated probes.
When should I not use it?
Do not use it if you only need a one-line summary of a single alert, or if you have no WAF/log access at all. It is also a poor fit when your problem is broader web intrusion triage without a SQL injection focus.
How to Improve detecting-sql-injection-via-waf-logs skill
Give tighter context up front
The best results come when you specify the WAF vendor, the time range, and the suspected target application. For example, say: “Analyze these AWS WAF logs from the last 6 hours for SQLi attempts against /api/login and /search, and separate blocked from allowed requests.” That is much stronger than “check for attacks.”
Include evidence the skill can actually classify
Provide raw payload fragments, rule IDs, and repeated source IPs when available. The detecting-sql-injection-via-waf-logs guide works better when it can compare patterns like UNION SELECT, INFORMATION_SCHEMA, or time-delay functions across multiple requests, because recurrence is often what turns a noisy alert into a credible campaign.
Watch for common failure modes
The main failure mode is overcalling benign strings that resemble SQL keywords. Another is under-reporting multi-stage attempts when the attack evolves from reconnaissance to exploitation. If the first output is too broad, ask for a narrower pass focused on one host, one attacker IP, or one rule family.
Iterate toward a Security Audit result
For Security Audit use, ask for a final output that separates confirmed SQLi, probable SQLi, and ambiguous noise, then request a short evidence table with timestamps, source IPs, targets, and matched patterns. That format makes detecting-sql-injection-via-waf-logs more actionable for review, ticketing, and rule tuning.