AI in App Security: Friend or Foe in 2025?

AI in App Security: Friend or Foe in 2025?

It's 2025, and AI (Artificial Intelligence) is everywhere, including how we protect our apps. But here's the tricky part: AI is like a super-smart tool that can be used for good and bad in application security (AppSec). It's changing the game for both those trying to break into apps and those trying to protect them.

Bad Guys Love AI Too

The same cool AI that helps us can also help cybercriminals. Here's how:

  • Super Sneaky Scams: AI can create fake emails, messages, and even voice or video (deepfakes) that look and sound incredibly real. Imagine getting a fake video call from your boss asking for urgent money – AI can make that happen!
  • Smarter Computer Viruses: Crooks use AI to build malware (like viruses) that can change and hide from normal security software.
  • Finding Weak Spots Faster: AI can quickly scan app code to find security holes, giving hackers a head start to attack.
  • More Ways to Attack: When companies add AI to their apps (like chatbots or AI tools), these new AI parts can also become targets if not secured properly.

Good Guys Fight Back with AI

Luckily, security folks are also using AI to make apps safer:

  • Spotting Trouble Quicker: AI can watch app activity 24/7 and spot weird patterns that might mean an attack is happening, often faster than a human could.
  • Automatic Defense: When AI spots a problem, it can automatically take steps to stop it, like blocking a hacker or shutting down a risky part of the app.
  • Building Safer Apps: AI can help developers find and fix security problems in their code before an app is released.
  • Catching Insider Threats: AI can learn how people normally use an app and flag strange behavior, which could mean an employee's account is compromised or being misused.

Staying Safe in the Age of AI

So, what do we do since AI plays for both teams?

  • Expect AI Attacks: We need security that knows AI will be used against it and can fight back.
  • Protect Your Own AI: If your app uses AI, make sure the AI itself is secure. Hackers might try to trick it or steal it.
  • People Still Matter: AI is a great helper, but we still need smart security people to make decisions and spot things AI might miss. Training is key.
  • Trust No One (Automatically): Assume any request or connection could be risky until proven safe. This is called "Zero Trust."
  • Lock Down APIs: Many AI tools connect through APIs (ways for different software to talk to each other). These APIs need strong security.

AI definitely makes app security more complicated. Hackers have new tricks, but defenders have new tools too. The best way forward is to keep learning, stay alert, and use AI wisely to protect our apps.

AI's dual role in cybersecurity is crucial to understand. How are you ensuring your teams can effectively balance AI's benefits with the potential risks it introduces?

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Tarak ☁️

building infracodebase.com - AI that learns from your docs, diagrams & codebase to help teams manage and scale infrastructure with context and security in mind.

4mo

Appreciate the balanced framing, Swapnil! AI is absolutely becoming both a defensive asset and an attacker’s force multiplier. I’ve been thinking a lot about how attackers are leveraging LLMs not just for phishing and payload obfuscation, but also for automation of reconnaissance, rapid mutation of scripts to evade static detection, and even chaining of API misuses in ways that used to require human creativity. On the flip side, AI-powered anomaly detection is promising, but the devil’s in the details. Models need access to clean baselines, relevant telemetry, and ideally application-layer context (auth flows, business logic boundaries) to avoid drowning in false positives. Without robust data labeling and feedback loops, even the best detection models end up being shelfware. Would love to dive deeper into how teams are managing trust boundaries between AI-generated recommendations and actual enforcement decisions. AI that flags is helpful but AI that auto-blocks based on opaque logic is a risky leap unless there's explainability and override mechanisms built in.

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Rob McGowan

President @ R3 | Robust IT Infrastructures for Scaling Enterprises | Leading a $100M IT Revolution | Follow for Innovative IT Solutions 🎯

5mo

Friend or Foe? - It's both Swapnil Deshmukh! Perhaps quantum computing will be the same way in a few years

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