Significance of API and Cloud Security

🚨SaaS-to-SaaS API Security: A Critical Priority in the Era of Increasing Data Breaches 🚨 The recent compromise of over 35 Chrome extensions, exposing sensitive data of more than 2.6 million users, serves as a wake-up call for all of us in the SaaS ecosystem. While the attack targeted browser extensions, the lessons learned are deeply relevant to SaaS-to-SaaS API integrations. Here’s why: 1️⃣ Entry Points for Attackers Just as compromised extensions allowed attackers to steal cookies, access tokens, and identity data, vulnerable SaaS APIs can become gateways for bad actors to infiltrate interconnected platforms. APIs with excessive permissions or weak security controls are high-value targets. 2️⃣ Far-Reaching Impact The Chrome extension breach affected millions, highlighting the scale of damage a single compromised entry point can cause. In a SaaS context, the ripple effect of a breached API could jeopardize data across multiple platforms and organizations. 3️⃣ Common Attack Vectors The use of phishing and malicious code injection in the Chrome attack mirrors tactics that could target SaaS APIs. Vigilance in identifying unusual API activity and securing credentials is non-negotiable. 🔐 What Can We Do? • Continuously monitor SaaS-to-SaaS connections: Audit APIs regularly and understand and limit the permissions granted to each API to avoid unnecessary risks. • Monitor for Suspicious Behavior: Deploy tools that flag unusual API traffic or unauthorized data access. • Educate Teams: Ensure everyone understands the risks, especially around phishing attempts and API misuse. The interconnected nature of SaaS solutions is a double-edged sword—unlocking efficiency but also amplifying risk. Proactive security measures are essential to safeguard our platforms and data. Let’s prioritize SaaS-to-SaaS API security and build a safer digital ecosystem together! 🌐💪 #Cybersecurity #SaaS #API #DataSecurity #TechLeadership

60% of companies reported a data breach within the last two years, and 74% had at least three API-related breaches. This shows the importance of enhanced API security because it exposes the business logic and data to an external system. Hackers love APIs because they're everywhere, and in many cases, they lack security while containing valuable data. Here is some advice on how to secure the design of your API: ▪️ First, you must know how many APIs are running in your ecosystem. You can use automated discovery tools to inventory them. ▪️ Authorization and authentication are crucial. Implement strong authentication and authorization mechanisms: one public key(access key) + one private key (secret key). ▪️ Signature Generation. Verify the authenticity and integrity of API requests. A critical step in this process is using HTTPS, a secure communication protocol, to encrypt data transmitted over your API. This ensures that the data is protected from unauthorized access during transmission. ▪️ For comprehensive security, HTTP requests should include the following parameters: authentication credentials to verify the user's identity, a timestamp to prevent replay attacks, request-specific data to specify the action to be performed, and nonce to avoid duplication requests. ▪️ Remember versioning. Not updated or outdated components make your applications vulnerable. ▪️ Security must be part of your team's awareness. Every member should be trained on the best practices for API security. ▪️ Implement monitoring and behavioral analysis tools, looking for anomalies in API traffic patterns. ▪️ Don't forget to adapt regular penetration testing to fix uncovered issues. Your API security cannot be an issue at the end of the SDLC but must be part of the API's design. Each stage of the cycle, as well as each component and functionality, poses a risk. The greater the complexity, the greater the threats. Image Credit: Munaim Naeem #Technology #APISecurity #DevOps

AI is not failing because of bad ideas; it’s "failing" at enterprise scale because of two big gaps: 👉 Workforce Preparation 👉 Data Security for AI While I speak globally on both topics in depth, today I want to educate us on what it takes to secure data for AI—because 70–82% of AI projects pause or get cancelled at POC/MVP stage (source: #Gartner, #MIT). Why? One of the biggest reasons is a lack of readiness at the data layer. So let’s make it simple - there are 7 phases to securing data for AI—and each phase has direct business risk if ignored. 🔹 Phase 1: Data Sourcing Security - Validating the origin, ownership, and licensing rights of all ingested data. Why It Matters: You can’t build scalable AI with data you don’t own or can’t trace. 🔹 Phase 2: Data Infrastructure Security - Ensuring data warehouses, lakes, and pipelines that support your AI models are hardened and access-controlled. Why It Matters: Unsecured data environments are easy targets for bad actors making you exposed to data breaches, IP theft, and model poisoning. 🔹 Phase 3: Data In-Transit Security - Protecting data as it moves across internal or external systems, especially between cloud, APIs, and vendors. Why It Matters: Intercepted training data = compromised models. Think of it as shipping cash across town in an armored truck—or on a bicycle—your choice. 🔹 Phase 4: API Security for Foundational Models - Safeguarding the APIs you use to connect with LLMs and third-party GenAI platforms (OpenAI, Anthropic, etc.). Why It Matters: Unmonitored API calls can leak sensitive data into public models or expose internal IP. This isn’t just tech debt. It’s reputational and regulatory risk. 🔹 Phase 5: Foundational Model Protection - Defending your proprietary models and fine-tunes from external inference, theft, or malicious querying. Why It Matters: Prompt injection attacks are real. And your enterprise-trained model? It’s a business asset. You lock your office at night—do the same with your models. 🔹 Phase 6: Incident Response for AI Data Breaches - Having predefined protocols for breaches, hallucinations, or AI-generated harm—who’s notified, who investigates, how damage is mitigated. Why It Matters: AI-related incidents are happening. Legal needs response plans. Cyber needs escalation tiers. 🔹 Phase 7: CI/CD for Models (with Security Hooks) - Continuous integration and delivery pipelines for models, embedded with testing, governance, and version-control protocols. Why It Matter: Shipping models like software means risk comes faster—and so must detection. Governance must be baked into every deployment sprint. Want your AI strategy to succeed past MVP? Focus and lock down the data. #AI #DataSecurity #AILeadership #Cybersecurity #FutureOfWork #ResponsibleAI #SolRashidi #Data #Leadership

Microsoft Takes Legal Action Against AI Hacking Group In a move to protect its AI services, Microsoft has filed a lawsuit against a foreign-based hacking group that exploited its generative AI platforms. The tech giant discovered that the group was using sophisticated software to access customer accounts illegally and alter the capabilities of AI services like Azure OpenAI[1]. The hackers developed a hacking-as-a-service infrastructure, selling access to compromised AI services along with instructions on how to generate harmful content. They used stolen API keys and customer authentication information to breach Microsoft's systems and create offensive images using DALL-E[1]. This incident highlights the critical importance of API key security: 1. Protect Your Keys - API keys are like passwords for your applications. Treat them with the same level of security you would any sensitive credential. 2. Regularly Rotate Keys - Implement a policy to change API keys periodically to minimize the impact of potential breaches. 3. Monitor Usage - Keep a close eye on API usage patterns to detect any unusual activity that could indicate compromised keys. 4. Implement Access Controls - Use the principle of least privilege when assigning API permissions to limit potential damage if keys are stolen. 5. Secure Storage - Never store API keys in public repositories or unsecured locations. Use secure vaults or environment variables instead. As AI technologies continue to advance, so do the tactics of malicious actors. It's crucial for both companies and individuals to remain vigilant and prioritize the security of their API keys and other sensitive credentials[1]. [1] https://lnkd.in/geSRNe4m

Enabling AI is only half the battle—securing it is just as critical. The McHire incident is a powerful reminder of what can go wrong when API security is neglected. McDonald’s AI-powered hiring platform left admin accounts protected by the default password “123456” and failed to enforce proper API permissions. Even more concerning, the platform was vulnerable to an Insecure Direct Object Reference (IDOR) flaw—meaning anyone could manipulate a record number in the API to access the personal data and chat transcripts of other applicants. As a result, over 64 million job applications were exposed within minutes. This shows how two basic but critical issues—weak passwords and IDOR vulnerabilities—can turn innovation into a liability. Every AI-powered system must prioritize API security from day one. Robust authentication, strict authorization, and real-time monitoring are non-negotiable for any endpoint handling sensitive data. As organizations accelerate AI adoption, remember—AI can only deliver value if it’s trusted and secure. Building smarter systems means building safer systems. Security and enablement must always go hand in hand. #AISecurity #APISecurity #Cequence

APIs Drive the Majority of Internet Traffic and Cybercrimals are Taking Advantage Application programming interfaces (APIs) are the connective tissue behind digital modernization, helping applications and databases exchange data more effectively. The State of API Security in 2024 Report from Imperva, a Thales company, found that the majority of internet traffic (71%) in 2023 was API calls. What's more, a typical enterprise site saw an average of 1.5 billion API calls in 2023. The expansive volume of internet traffic that passes through APIs should be concerning for every security professional. Despite best efforts to adopt shift-left frameworks and SDLC processes, APIs are often still pushed into production before they're cataloged, authenticated, or audited. On average, organizations have 613 API endpoints in production, but that number is rapidly expanding as pressure grows to deliver digital services to customers more quickly and efficiently. Over time, these APIs can become risky, vulnerable endpoints. In their report, Imperva concludes that APIs are now a common attack vector for cybercriminals because they're a direct pathway to access sensitive data. As a matter of fact, a study from the Marsh McLennan Cyber Risk Analytics Center finds that API-related security incidents cost global businesses as much as $75 billion annually. https://lnkd.in/g9nFmYge #CyberSecurity #API #cybercrime

We need to talk about a growing security threat: While AI is invaluable to developers, it’s also been a boon to hackers. State-backed actors from China, Russia and Iran have been using OpenAI tools to sharpen their skills and deceive targets. The vast majority of hackers agree that businesses adopting AI have created new attack vectors. One particular vulnerability is APIs — the doors and windows into code that allow apps to “talk” to each other are increasingly being exploited. In the past two years, 60% of organizations have been hit by an API security breach. Fighting back requires businesses to take stock of their APIs to detect and prevent attacks. The key steps: doing an API inventory, ensuring that APIs meet specific security standards and using smart tools to spot threats. Equally important is integrating security into the developer pipeline. This “shift left” isn’t new, but we’ll see it continue to strengthen — part of a broader effort to close the gap between Dev and other functions such as FinOps and CI/CD delivery. I don’t mean that every developer will be tasked with security. Instead, this job will fall to dedicated engineering teams. For example: in an organization with 100 developers, expect five or ten to focus on security. For software developers, big opportunities lie ahead and growing threats. Teams that stay vigilant and take advantage of the best tools will be better positioned to see real productivity gains from AI and avoid the security and quality pitfalls. More in my latest newsletter.

Third-party applications are essential to modern business operations. But with great connectivity comes great responsibility. Think of your third-party apps as doors, and your sensitive data as what moves through them. You can install the strongest locks (secure APIs), but if you're not watching what's coming and going, you're leaving your house vulnerable. At Vorlon, we believe your third-party ecosystem deserves the same proactive security coverage as endpoints, networks, and the cloud. Why? Because breaches originating from third-party apps are increasing at an alarming rate - 68% year over year, according to the Verizon DBIR. Take the BeyondTrust breach as an example. This breach, which impacted organizations like the U.S. Treasury, demonstrated how attackers used stolen API keys to escalate privileges and access sensitive data. It exposed a harsh reality: most organizations lack the necessary visibility and control over their third-party application ecosystems, leaving them vulnerable to exploitation. The question I encourage every business leader to ask today is this: How confident are you that your sensitive data is safe as it flows through your third-party ecosystem? If the answer isn't clear, it's time to rethink your strategy. Check out Jonathan Reshef's blog for a deeper dive, link is in the comments! #thirdpartyapplicationsecurity #detectionandresponse #TADR #APIsecurity #Vorlon

APIs are helping enterprises grow faster. They unlock additional revenue, entry into newer markets, and aggressive capture of current markets. But they’re also where most enterprises are bleeding margin. Without API security built in, the growth they create gets eaten up by: 1. Production fire drills 2. Incident response costs 3. Compliance fines 4. Breach recovery 5. Bloated security teams trying to catch up 6. Incomplete yet expensive pen-testing So while APIs are driving revenue, the lack of security is stopping that revenue from becoming profit. And the risk is growing. Most of your business logic, sensitive data, and authentication layers already do. The problem? Developers build for users. They optimize for experience, not necessarily defense against exploitation. Hackers don’t think like users. They look for the fastest way in: shortcuts, misconfigurations, and unauthenticated endpoints. What feels seamless onboarding to a user often looks like a wide open door into the enterprise network to an attacker. And when APIs are breached in BFSI, fintech, or healthcare, it’s not just a ticket. It’s a public disclosure. A regulatory probe. A multi-million dollar fine. This is why API Security isn’t a good-to-have vitamin but a necessary painkiller for those who want to survive and thrive in the API-First world. The only way forward is to embed security where the APIs originate: with developers. To secure them as they’re built, not after they break. Take a look ⬇️ Mehmet Gonullu #cybersecurity #apis #enterprisesecurity #applicationsecurity