SKILLS/implementing-runtime-application-self-protection/SKILL.md
Deploy Runtime Application Self-Protection (RASP) agents to detect and block attacks from within application runtime, covering OpenRASP integration, attack pattern detection, and security policy configuration for Java and Python web applications.
npx skillsauth add pinkpixel-dev/skills-collection-2 implementing-runtime-application-self-protectionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Runtime Application Self-Protection (RASP) instruments application code at runtime to detect and block attacks by examining actual execution context rather than relying solely on network traffic patterns. Unlike WAFs that inspect HTTP requests externally, RASP agents intercept dangerous operations (SQL queries, file operations, command execution, deserialization) at the function level inside the application, achieving near-zero false positives. This skill covers deploying OpenRASP for Java applications, configuring detection policies for OWASP Top 10 attacks, tuning alerting thresholds, and integrating RASP telemetry with SIEM platforms.
Install the RASP agent into the application server runtime using JVM agent attachment for Java or middleware hooks for Python.
Define detection rules for SQL injection, command injection, SSRF, path traversal, XXE, and deserialization attacks with block or monitor actions.
Run the agent in monitor mode during normal operations to establish baseline behavior and tune policies to reduce false positives before switching to block mode.
Forward RASP alerts to the SIEM for correlation with WAF, IDS, and authentication events to build comprehensive attack timelines.
JSON report containing RASP policy audit results, detected attack attempts with stack traces, blocked requests summary, and coverage assessment against OWASP Top 10.
tools
Perform lateral movement across Windows networks using WMI-based remote execution techniques including Impacket wmiexec.py, CrackMapExec, and native WMI commands for stealthy post-exploitation during red team engagements.
data-ai
Detects lateral movement techniques including Pass-the-Hash, PsExec, WMI execution, RDP pivoting, and SMB-based spreading using SIEM correlation of Windows event logs, network flow data, and endpoint telemetry mapped to MITRE ATT&CK Lateral Movement (TA0008) techniques.
tools
Kubernetes penetration testing systematically evaluates cluster security by simulating attacker techniques against the API server, kubelet, etcd, pods, RBAC, network policies, and secrets. Using tools
testing
Assess the security posture of Kubernetes etcd clusters by evaluating encryption at rest, TLS configuration, access controls, backup encryption, and network isolation.