DevOps & Cloud
4,382 results
- Configuring AWS Verified Access For ZtnaMahipalConfigure AWS Verified Access to provide VPN-less zero trust network access to internal apps, combining identity trust providers (IAM Identity Center, Okta/OIDC), device posture providers (CrowdStrike, Jamf), Cedar policy authoring, and Terraform deployment.
- Configuring Identity Aware Proxy With Google IapMahipalConfigures Google Cloud Identity-Aware Proxy (IAP) via gcloud to enforce per-request identity verification on Compute Engine, App Engine, Cloud Run, and GKE, including IAM bindings, Access Context Manager access levels, session/reauth settings, and service-account programmatic access.
- Configuring Multi Factor Authentication With DuoMahipalDeploys Cisco Duo multi-factor authentication across enterprise applications, VPN, RDP, and SSH access points, covering Duo Authentication Proxy setup, adaptive authentication policies, device trust assessment, and phishing-resistant WebAuthn/FIDO2 deployment aligned with NIST 800-63B AAL2/AAL3. Use when adding or hardening MFA for remote access, VPN, or privileged logins with Duo.
- Configuring Pfsense Firewall RulesMahipalConfigures pfSense firewall rules, NAT policies, IPsec/OpenVPN tunnels, and traffic shaping to enforce network segmentation and control traffic between zones such as DMZ, internal, guest, and IoT. Use when deploying a pfSense perimeter or internal firewall, setting up port-forwarding NAT, configuring site-to-site or remote-access VPNs, or applying QoS/bandwidth policies.
- Configuring Snort Ids For Intrusion DetectionMahipalInstalls, configures, and tunes Snort 3 to monitor network traffic for malicious activity using custom and community rulesets, preprocessors, and alert output plugins. Use when deploying network-based intrusion detection at key boundaries, writing custom Snort rules, tuning rulesets to reduce false positives, or integrating Snort alerts with a SIEM.
- Defending Llms With GuardrailsMahipalDeploys Llama Guard 3 safety classification, NeMo Guardrails programmable dialogue rails, and LLM Guard input/output scanner pipelines as complementary runtime defenses that inspect and constrain LLM prompts and responses.
- Deploying Decoy Files For Ransomware DetectionMahipalDeploys canary files (honeytokens) across file systems to detect ransomware encryption activity in real time. Uses strategically placed decoy documents monitored via file integrity monitoring or OS-level watchdogs to trigger alerts when ransomware modifies or encrypts them.
- Deploying Honeytokens And CanarytokensMahipalPlants Canarytokens-based decoy artifacts (honey credentials, DNS tokens, web-bug URLs, AWS keys, documents, kubeconfigs) using Thinkst's open-source Canarytokens project and alerts via email or webhook when a token is touched. Use for high-fidelity intrusion detection in low-telemetry areas like file shares or credential stores, or to catch credential dumping and data-theft staging.
- Deploying Ransomware Canary FilesMahipalDeploys and monitors ransomware canary files using Python's watchdog library, placing decoy files mimicking high-value targets (financial records, credentials, database exports) where ransomware enumerates first, and alerting via email, Slack, or syslog on any read/modify/rename/delete.
- Deploying Software Defined PerimeterMahipalDeploys a Software-Defined Perimeter per the CSA v2.0 specification, configuring Single Packet Authorization, mutual TLS, and SDP controller/gateway components to enforce zero trust network access. Use when building or hardening zero trust network architecture, implementing SPA-based "invisible" infrastructure that cloaks services from unauthenticated scanning, or meeting compliance requirements…
- Deploying Tailscale For Zero Trust VpnMahipalDeploys and configures Tailscale (or self-hosted Headscale) as a WireGuard-based zero trust mesh VPN, setting up identity-aware ACLs, exit nodes, subnet routers, and MagicDNS for encrypted peer-to-peer connectivity. Use when replacing traditional VPN servers with an identity-authenticated mesh network or enforcing granular per-device access control lists.
- Detecting Ai Model Prompt Injection AttacksMahipalDetects prompt injection using regex signature matching, heuristic scoring for structural anomalies, and DeBERTa-based transformer classification, flagging direct injections (system-prompt overrides, role-play escapes) and indirect injections (encoded payloads, obfuscation) per OWASP LLM Top 10 (LLM01:2025).
- Detecting Anomalies In Industrial Control SystemsMahipalDeploys anomaly detection for OT/ICS environments using machine learning on OT network baselines, physics-based process models, and Modbus/DNP3/OPC UA traffic analysis to flag deviations, rogue devices, and mismatches against historian data.
- Detecting Arp Poisoning In Network TrafficMahipalDetect Layer 2 ARP poisoning/spoofing by deploying ARPWatch, Dynamic ARP Inspection (DAI), Wireshark packet analysis, and custom Python monitoring scripts that flag gratuitous ARP floods, IP-to-MAC mapping changes, and duplicate IP addresses.
- Detecting AWS Cloudtrail AnomaliesMahipalDetect unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.
- Detecting AWS Iam Privilege EscalationMahipalDetect AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege violations
- Detecting Business Email Compromise With AiMahipalDeploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.
- Detecting Container Drift At RuntimeMahipalDetects unauthorized runtime drift in containers by monitoring binary execution, filesystem changes, and configuration deviation from the original immutable image, using Falco and Microsoft Defender for Containers.
- Detecting Data And Model PoisoningMahipalIdentify poisoned training data and backdoored ML models across the pipeline using IBM's Adversarial Robustness Toolbox (activation clustering, spectral signatures, trigger reconstruction), Cleanlab for label-quality issues, and supply-chain checks like weight-hash verification and safetensors enforcement.
- Detecting Dll Sideloading AttacksMahipalDetect DLL side-loading and search-order hijacking (MITRE T1574) where adversaries plant malicious DLLs for legitimate signed applications to load, by analyzing Sysmon Event ID 7 DLL-load events, checking signatures/hashes against known-good versions, and flagging path anomalies with EDR tools like CrowdStrike, MDE, or SentinelOne.
- Detecting Dns Exfiltration With Dns Query AnalysisMahipalDetect data exfiltration via DNS tunneling (tools like iodine, dnscat2, dns2tcp) by analyzing query entropy, subdomain length, query volume to single domains, TXT/CNAME/NULL record abuse, and oversized response payloads using passive DNS monitoring and statistical/ML methods. Use when hunting for covert DNS-based data exfiltration or building a passive DNS anomaly detection capability.
- Detecting Email Forwarding Rules AttackMahipalDetect malicious inbox/mail-flow forwarding rules that adversaries create to maintain persistent access to email communications for intelligence collection and business email compromise. Use when hunting for suspicious auto-forwarding, hidden mailbox rules, or T1114-style email collection persistence after a compromised account or BEC incident.
- Detecting Entra Offensive Tools In Graph LogsMahipalHunt AADGraphActivityLogs and MicrosoftGraphActivityLogs in Microsoft Sentinel/Log Analytics using KQL to fingerprint offensive Entra ID enumeration tools such as ROADtools, AADInternals, and AzureHound, including User-Agent signatures, roadrecon endpoint sweeps, and sign-in correlation.
- Detecting Kerberoasting AttacksMahipalDetect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests (Event ID 4769) targeting service accounts with SPNs, which attackers request offline to crack service account passwords. Use when hunting for MITRE T1558 credential access activity or investigating suspected service account password cracking attempts in Active Directory Kerberos logs.