This is a structured image generation workflow for creating cyber security characters. The workflow includes steps such as facial identity mapping, tactical equipment outfitting, cybernetic enhancements, and environmental integration to produce high-quality, cinematic renders. After uploading your face and filling in the values in the fields, your prompt is ready. NOTE: The sample image belongs to me and my brand; unauthorized use of the sample image is prohibited.
1{2 "name": "Cyber Security Character",3 "steps": [4 {5 "step_1": "Facial Identity Mapping",6 "description": "Maintain 100% facial consistency based on the provided reference photos. Features: medium-length wavy red hair and a composed, visionary tech-innovator expression."7 },8 {9 "step_2": "Tactical Gear & Branding",10 "description": "Outfit the subject in a sleek red tactical jacket with intricate gold circuitry textures. Correctly integrate the '' name and the specific '' logo emblem onto the chest piece."11 },12 {13 "step_3": "Cybernetic Enhancement",14 "description": "Apply subtle, minimalist gold-accented cybernetic interface patterns onto the skin of the face, ensuring they blend naturally with the {Style:Cyberpunk} aesthetic."15 },16 {17 "step_4": "Environmental Integration",18 "description": "Design a background featuring the flag merged with glowing golden digital circuits. Include a distant cinematic futuristic skyline of a metropolis (Cyberpunk )."19 },20 {21 "step_5": "Lighting & Cinematic Render",22 "description": "Utilize warm, dramatic side lighting from the right to cast a soft silhouette onto the background. Render in 4K ultra-realistic quality with hyper-detailed textures."23 }24 ]25}
Reviews nginx.conf and site configs for security problems such as TLS 1.0/1.1, weak ciphers, missing HSTS and security headers, the add_header inheritance trap, alias off-by-slash path traversal, autoindex, unlimited body size, $uri in redirects, HTTP without an HTTPS redirect, open admin paths and logins without rate limits. Gives a fixed config. Includes a stdlib Python checker with --self-test.
Reviews a password policy config against NIST SP 800-63B-4, covering length minimums, no composition rules or forced expiry, blocklist checks, rate limiting, paste and Unicode support, no hints or security questions, and safe hashing parameters. Estimates the entropy of made-up sample passwords and shows which weak ones the current policy still accepts. Never asks for real passwords. Includes a stdlib Python checker with --self-test.
Reviews GitHub Actions workflow YAML for supply-chain and injection risks: pull_request_target with PR checkout, untrusted github.event text in run steps, actions pinned to tags or branches instead of commit SHAs, missing or write-all permissions, secrets in shell commands, curl | bash, self-hosted runners on PRs, and missing timeouts. Use before merging CI changes or auditing a repo. Includes a stdlib Python linter with --self-test.
Lints .env and .env.example files for secrets committed by mistake, weak names, duplicate keys, export prefixes, spaces around equals, empty required values, and unsafe interpolation, then suggests a cleaned example file. Use when a user asks "is this .env safe to commit?", "why won't dotenv load?", or "diff my .env.example". Includes a tested stdlib Python linter.
