Tips for Improving Security in Software Development

Things I would tell you about basic security engineering if I weren’t afraid of hurting your feelings: [1] If your app only works because nobody has attacked it yet, it is not secure. It is lucky. [2] “We will secure it later” usually means “we will learn during the incident.” [3] A public S3 bucket is not a cloud problem. It is an ownership problem. [4] If you do not know who owns an API key, rotate it today. [5] Your .env file should never be one bad Git push away from becoming public. [6] MFA is not advanced security. It is the seatbelt. [7] If every engineer has admin access, nobody has access control. [8] A scanner finding 900 issues is not progress. Knowing which 9 matter is progress. [9] If logs do not tell you who did what, when, and from where, you are blind. [10] A secret in Slack is still a secret leak. [11] AI-generated Terraform should be reviewed like code from someone with production access. [12] If your rollback plan is “we will figure it out,” you do not have a rollback plan. [13] Backups are useless until you have tested restore. [14] “Internal only” is not a security boundary. Internal systems get breached too. [15] If your CI/CD can deploy to prod, your CI/CD is production. [16] Least privilege hurts less than explaining why one token could access everything. [17] Your WAF is not a substitute for parameterised queries and sane backend logic. [18] If one tired engineer can delete prod, your process is the vulnerability. [19] Good security is usually boring: patching, logging, reviews, limits, rotation, backups. [20] The best security engineers are not the ones who block everything. They are the ones who understand risk, reduce blast radius, and help teams ship without leaving the doors open. Security is not about sounding scary. It is about building systems that survive tired humans, bad defaults, rushed launches, AI agents, and real attackers. If that sounds harsh, good. Production is harsher. And it keeps receipts. No mercy. -- 📢 Follow saed ‎if you enjoyed this post Join the security club: https://lnkd.in/efH2BqBn Newsletter: https://lnkd.in/evTTetXz Read more: https://lnkd.in/ew7W2DQ3

Security mistakes are never theoretical once secrets hit a repository The moment an API key is committed the problem is no longer about Git It is about incident response A lot of developers think the fix starts with removing the key from the codebase or rewriting Git history That matters But it is not the first priority The first priority is assuming the secret is already compromised Experienced engineers respond in this order → Revoke or rotate the exposed key immediately → Check logs and usage to detect abuse → Remove the secret from the codebase → Rewrite history if needed to reduce future exposure → Update deployment and environment variables safely → Add guardrails so it does not happen again This is one of the biggest mindset shifts from junior to senior engineering Juniors often focus on cleaning the evidence Seniors focus on limiting the blast radius Because once a secret is exposed you cannot confidently assume nobody saw it That is why secret management matters so much in professional systems Good teams build processes that reduce the chance of human mistakes becoming production incidents → Store secrets outside source code → Use environment variables or secret managers → Add pre commit hooks and secret scanning → Limit permissions for keys and tokens → Rotate secrets regularly → Treat every exposed key as compromised Security maturity is not about never making mistakes It is about responding correctly when mistakes happen If a secret was exposed in your team today would everyone know the right order of actions Share your thoughts below Follow Nelson Djalo for practical lessons that help developers think like real software engineers #coding #programming #softwareengineering

Most product founders (or aspiring founders) think cybersecurity is something that can be added on as we go. In 2024, 68 % of breaches involved a non‑malicious human element, like misconfigurations or coding oversights. Security isn’t a checkbox at launch; it’s a mindset woven into every sprint, every pull request, every architectural decision. Here’s a playbook we, at GrayCyan, have developed: 1️⃣. Threat Model Upfront Before you write a single line of code, map out your attack surface. What data are you storing? Who could target it, and how? A lightweight threat model (even a few whiteboard sketches) helps you prioritize controls around your riskiest assets. 2️⃣. Secure Design Patterns Adopt proven patterns—like input validation, output encoding, and the principle of least privilege—right in your prototypes. Whether it’s microservices or monolithic apps, enforcing separation of concerns and privilege boundaries early means fewer surprises down the road. 3️⃣. Shift‑Left Testing Integrate static analysis (SAST), dependency scanning, and secret‑detection tools into your CI/CD pipeline. Automate these checks so that every pull request tells you if you’ve introduced a risky dependency or an insecure configuration—before it ever reaches production. 4️⃣. Continuous Code Reviews Encourage a culture of peer review focused on security. Build short checklists (e.g., avoid hard‑coded credentials, enforce secure defaults) and run them in review sessions. Rotate reviewers so everyone gets exposure to security pitfalls across the codebase. 5️⃣. Dynamic & Pen‑Test Cycles Complement static checks with dynamic application security testing (DAST) and periodic penetration tests. Even a quarterly or biannual pen‑test will surface issues you can’t catch with automated scans—like business‑logic flaws or subtle authentication gaps. 6️⃣. Educate & Empower Your Team Run regular “lunch‑and‑learn” workshops on topics like OWASP Top 10, secure cloud configurations, or incident response drills. When developers think like attackers, they write more resilient code—and spot risks early. 7️⃣. Plan for the Inevitable No system is 100 % immune. Build an incident response plan, practice it with tabletop exercises, and establish clear escalation paths. That way, when something does go wrong, you move from panic to precision—minimizing impact and restoring trust. At GrayCyan, we partner with founders (and upcoming founders that have amazing product ideas) to embed these practices as we build apps. If you’re ready to turn security from an afterthought into your competitive advantage, let’s connect. Drop a comment or send us a DM, and let’s bake trust into your next release. #DevSecOps #SecureByDesign #SecureDevelopment #DataProtection #TechStartups GrayCyan AI Consultants & Developers

Shipping secure software in the age of open source + AI (a CTO’s friendly rant) I love open source. I like AI copilots. I also enjoy sleeping at night. Those can all co-exist if we treat security like a product feature, not a hope and a prayer. Here’s the playbook we use that keeps speed high and risk low: 1) Standards beat vibes AI can draft and OSS can accelerate, but our coding standards decide what ships. Keep them in-repo, short, and enforceable: auth, crypto, logging, errors, secrets, retries. Examples over essays. 2) “Do you understand this diff?” If you can’t explain a change in two sentences, it doesn’t merge. PRs must state intent, radius, data touched, and auth/perm impacts. Reviewers say what they tested and not “looks good.” AI-generated code still needs human brain cells. 3) Let robots be relentless Every commit runs Static Application Security Testing (SAST), dependency/Software Bill of Materials (SBOM) checks, license policy, and secrets detection. 4) Dynamic Application Security Testing (DAST) on deploy Spin up the env and point DAST at it: auth flows, input fuzzing, headers, cookies, rate limits. Block on criticals/highs; auto-ticket the rest. If staging can’t handle our scanner, it won’t handle theirs. 5) Pen tests by experts in the field For every major release, bring in an external pen test. Fix, retest, publish the delta. Fresh eyes > familiar blind spots. 6) Open source ≠ open season Curate approved packages and minimum versions. Generate an SBOM on every build and fail on banned/CVE’d deps. Watch for typosquats and weird transitive stuff (yes, we still remember left-pad). 7) Secrets: not in code, not in logs, not in CI Central secret store, rotation, short TTLs, least privilege. Friends don’t let friends .env in prod. 8) Threat model like adults (30 mins) New feature? List 3–5 abuse cases and one control each. Data class, authz paths, rate limits, input validation. Done is better than ornate. 9) Logs > vibes Security-minded logging (no PII dumps), trace IDs, anomaly alerts. Add a sane WAF and rate limits. At 3 a.m., “we think it’s fine” isn’t telemetry. 10) AI with seatbelts No secrets in prompts. Human review for anything touching auth, crypto, or persistence. Prefer vetted patterns over clever one-liners the model dreamed up. My “no-ship” gates ✅ Standards linted in CI ✅ PR intent + risk explained, reviewer confirms understanding ✅ SAST/Deps/SBOM/Secrets scans (fail on criticals/highs) ✅ DAST on deploy (block on criticals/highs) ✅ External pen test for every major change (with retest) ✅ Centralized secrets; no secrets in code/logs/CI ✅ Quick threat model per feature ✅ Telemetry + WAF + rate limits live and monitored Ship fast. Ship secure. Sleep better. And if a robot blocks your PR then thank it, fix it, and keep your weekend. ☕️🛡️ Want a one-pager you can paste into your pipeline? Happy to share. #AppSec #OpenSource #AI #DevSecOps #Security #SBOM #PenTest #DAST #SAST #CTO #bTrade

Day 9 of MCP Security: Top 9 dev checklist items to build secure MCP Servers- 1. Structure and sanitize all user input before adding to prompts → Avoid direct string interpolation. Use templating and clearly defined variables. 2. Register only essential tools and enforce tool-level access → No generic "call-anything" agents. Tools must be explicit, minimal, and reviewed. 3. Treat system prompts like code: versioned, reviewed, auditable → Store in Git. Require PRs. A one-line prompt change can cause a full policy failure. 4. Log full agent context and decisions: prompt → context → tool → output → This is your only audit trail. Without it, you’re blind during incidents. 5. Write automated prompt tests in CI (edge cases, malicious inputs, reasoning traps) → Prompt failures are business logic failures. Catch them before prod. 6. Scrub sensitive data from injected context and agent memory → No tokens, PII, internal notes. Memory must be minimal and expirable. 7. Gate high-impact actions with review or confidence thresholds → No auto-refunds, mass updates, or API writes without safety logic. 8. Default to inaction when the model is uncertain or underinformed → Build the "safe failure" path - defer to human, escalate, or log-and-stop. 9. Disable unused tools and unexposed APIs by default → Every tool the agent can “see” is a surface. Keep tool registration lean and explicit. No unvetted access.

Security can’t be an afterthought - it must be built into the fabric of a product at every stage: design, development, deployment, and operation. I came across an interesting read in The Information on the risks from enterprise AI adoption. How do we do this at Glean? Our platform combines native security features with open data governance - providing up-to-date insights on data activity, identity, and permissions, making external security tools even more effective. Some other key steps and considerations: • Adopt modern security principles: Embrace zero trust models, apply the principle of least privilege, and shift-left by integrating security early. • Access controls: Implement strict authentication and adjust permissions dynamically to ensure users see only what they’re authorized to access. • Logging and audit trails: Maintain detailed, application-specific logs for user activity and security events to ensure compliance and visibility. • Customizable controls: Provide admins with tools to exclude specific data, documents, or sources from exposure to AI systems and other services. Security shouldn’t be a patchwork of bolted-on solutions. It needs to be embedded into every layer of a product, ensuring organizations remain compliant, resilient, and equipped to navigate evolving threats and regulatory demands.

𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐚 “𝐟𝐞𝐚𝐭𝐮𝐫𝐞” - 𝐢𝐭’𝐬 𝐚 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧. Whether you’re building a simple app or a complete enterprise system, security must live at the core of your software development process. In today’s world of constant cyber threats, data leaks, and system vulnerabilities, a single weak point can cost a business its reputation, users, and even legal compliance. That’s why security needs to be part of every stage of the SDLC - from planning to deployment and long-term maintenance. 💡 𝐒𝐨 𝐰𝐡𝐲 𝐢𝐬 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭? Protects sensitive data (confidentiality) Ensures data integrity and reliability Keeps systems available and resilient Builds user trust and brand credibility Reduces long-term cost by preventing breaches Helps meet compliance and regulatory standards 🔧 𝐖𝐡𝐞𝐫𝐞 𝐝𝐨𝐞𝐬 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐟𝐢𝐭 𝐢𝐧 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭? 𝐄𝐯𝐞𝐫𝐲𝐰𝐡𝐞𝐫𝐞. In planning, we identify risks. In design, we choose secure architecture. In coding, we follow secure coding practices. In testing, we run security scans and penetration tests. In deployment, we secure servers, APIs, and credentials. In maintenance, we patch and monitor continuously. 🔒 𝐇𝐨𝐰 𝐝𝐨 𝐰𝐞 𝐬𝐞𝐜𝐮𝐫𝐞 𝐨𝐮𝐫 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞? Some key approaches: Secure coding & code reviews Input validation and protection against common attacks Proper authentication & authorization Cloud & infrastructure security (firewalls, API Gateway, secrets management) DevSecOps: embedding security into CI/CD Encryption for data at rest and in transit Role-based access control & MFA Regular vulnerability scanning & penetration testing Clear security policies and team awareness At the end of the day, security is not a checkbox - it’s a culture. If we build with security in mind from day one, we build software that users trust and businesses can rely on.

Your infrastructure looks fine right now. Every dashboard is green. Every deploy goes through. No alerts firing. But somewhere underneath, a manual change from 3 months ago is waiting to take down production. That is infrastructure drift. Someone tweaks a security group by hand. Someone changes a database config through the console. Small fix. No big deal. Until 40 of those stack up and nobody knows the real state of anything. Organizations with high configuration drift take 60% longer to recover during incidents. The first thing you lose is trust in your own systems. 5 patterns that stop it: 1. Treat infrastructure like application code. Every change goes through Git. Every change gets a pull request. Every change has an audit trail. If it didn't go through a PR, it didn't happen. 2. Lock down your state files. Your state file contains resource IDs, configs, and sometimes credentials. Encrypt it. Restrict access. Version it. Never commit state files to Git. 3. Build security INTO your modules, not on top. Every module ships with least-privilege defaults. IAM roles that only grant what the resource actually needs. Security groups that default to deny-all. Security added later is security forgotten later. 4. Run infrastructure through CI/CD like app code. Static analysis catches syntax errors. Security scanners catch misconfigurations. Automated tests validate modules work together. All before it touches production. 5. Make your infrastructure self-documenting. prod-ecommerce-api-postgres-primary tells you everything. pg-01 tells you nothing. Tag everything: env, owner, cost center, compliance tier. Untagged resources are invisible resources. The goal is not perfect infrastructure. The goal is infrastructure you can trust. Trust that what you see is what you have. Trust that changes are tracked. Trust that security is enforced, not assumed. At NextLinkLabs.com, we help engineering teams get there. Subscribe to the newsletter for weekly lessons on building better software and smarter infrastructure: https://lnkd.in/efpcmnTk

🚨In the AI era, software moves at machine speed. So do supply chain attacks. The npm axios compromise, the enormously popular JavaScript http client with over 300 million weekly downloads, is a sharp reminder of what has changed. This was not typo-squatting. Not a fake package. Not a random dependency buried deep in the graph. This was compromise through a trusted path in the real software supply chain. That is the point leaders need to internalize. The problem is no longer just whether developers write secure code. It is whether the systems, packages, and automation they rely on can still be trusted when software is being assembled, shipped, and updated at machine speed. A short exposure window is all it takes. One compromised package. One CI run. One developer machine. One production workflow. That is enough. A few things every engineering and security leader should be driving right now: 1. Pin exact versions. Stop relying on loose defaults. 2. Enforce lockfiles and deterministic builds in CI/CD. 3. Block install scripts wherever they are not explicitly required. 4. Scan continuously for malicious and tampered dependencies, not just known vulnerabilities. 5. If you were exposed, assume compromise. Isolate, rebuild, and rotate secrets. Do not just patch and move on. Software supply chain security is no longer a developer hygiene issue. It is a leadership issue. It is operational resilience. It is trust. And increasingly, it is board level. The teams that get ahead here will not be the ones reacting fastest after the next incident. They will be the ones that built the controls before it happened. For security and engineering leaders: what is the single control you trust most right now against this class of attack? #SupplyChainSecurity #OpenSourceSecurity #DevSecOps #Cybersecurity #npm Snyk

Shift left is NOT dead! It’s just become misunderstood for some reason. Let’s clear it up: Shift left in cybersecurity simply means adding security habits earlier in the software development lifecycle (SDLC). It means implementing proactive security habits closer to design and coding, rather than ONLY reacting once software is already in production. But here’s the key: To shift left effectively, you should first "start right". Start Right: Build visibility, monitoring, and resilience in production - Monitor for real-world threats and attacks - Respond to and fix actual exploitable production vulnerabilities (found via pentests and bug bounty findings) - Track the cost and impact of security incidents Then, use root cause analysis to connect these incidents to upstream opportunities for prevention, so you can make the case for... Shift Left: Move prevention and awareness earlier in the lifecycle - Conduct architecture reviews and regular threat modeling - Define security requirements and apply secure coding practices - Deliver secure code training - Implement pre-production scanning (SAST, SCA, etc.) Once both the right-side and left-side controls are in place, you have successfully shifted "everywhere" - the ultimate goal! But let’s be clear: “Shift everywhere” does NOT mean pushing the security responsibilities onto the developers. It means building effective security controls into the SDLC itself, with well defined shared responsibilities across: - Developers - Security - Product and Project Managers - Engineering leaders …and anyone else involved in shipping software This all will require CHANGE to your organization's habits and culture, which takes time, and a whole lot of patience. You’ll need allies. You’ll need security champions. Your security team can’t do this alone. Start right → Shift left → Shift everywhere! #applicationsecurity #productsecurity #softwaresecurity #securitychampions #securityculture #proactivesecurity #devsecops #developerexperience #shiftleft #shifteverywhere #sdlc