Redefining Mobile Bot Defense For the AI Era

AI Has Changed the Mobile Attack Landscape Forever

Mobile apps today are under siege from a new wave of highly sophisticated attacks. Deepfakes, automated account takeovers (ATOs), AI-generated synthetic users, and targeted social engineering campaigns are no longer fringe threats — they are daily realities for mobile businesses across every industry. The volume and sophistication of mobile bot attacks are rising fast.

The volume and sophistication of mobile bot attacks are rising fast. Bots now account for nearly half of all internet traffic, and malicious bots make up more than 32% of that volume. According to The Hacker News, bot-driven fraud and insecure APIs are now costing businesses as much as $186 billion annually, underscoring the urgency for stronger mobile protections.
To meet this challenge, Appdome has reimagined mobile bot defense from the ground up. With the latest advancement of MobileBOT™ Defense, mobile brands can now deploy 400+ dynamic protections inside any Android or iOS app, turning existing web application firewalls (WAFs) into real-time fraud-fighting engines without adding SDKs, servers, agents, or complexity.
This new approach is designed to stop the most advanced forms of mobile fraud — including deepfake attacks, mobile malware, session hijacking, synthetic account creation, automated KYC abuse, and much more — before they ever reach backend infrastructure.

The Rapid Rise of AI-Driven Mobile Threats

AI has permanently changed the threat landscape for mobile apps. Bot attacks are no longer confined to simple brute force or credential stuffing attempts. Unlike traditional web bots that interact directly with backend services, many mobile bot attacks occur inside the app itself — spoofing gestures, abusing device sensors, or mimicking legitimate user behavior without triggering obvious backend anomalies. These threats don’t behave like conventional web bots and can’t be reliably detected by WAFs or backend monitoring tools alone. Today’s adversaries leverage AI and automation to:

• Bypass biometric checks using face cloning, liveness spoofing, and deepfake images
• Automate fraudulent signups using synthetic identities and fake or virtualized device environments
• Hijack sessions during login, payment, and password reset flows using mobile malware and spyware that is used to gain highly privileged access to mobile accounts.
• Mimic real users with fake taps, swipes, and gestures to commit on-device fraud.
• Exploit mobile APIs to bypass traditional KYC enforcement mechanisms at critical points in the user flow — including account creation, password resets, and authentication flows like MFA bypass.

These threats evolve constantly, using polymorphic techniques and social engineering to evade static defenses. Traditional anti-bot and WAF-based protections, built for web environments and older attack models, are no match for this unprecedented level of automation and sophistication.
Modern mobile bot attacks blend invisibly into real user flows, manipulating mobile apps themselves to look legitimate while committing fraud at scale. Without in-app, AI-native defenses, mobile businesses are left vulnerable. Effective defense requires observing and responding to threats within the mobile runtime.

Why Traditional Mobile Bot Defenses Fall Short

Traditional mobile bot defenses were never designed for the modern, app-centric, API-driven world if mobile. Most were adapted from web-based solutions and rely heavily on SDKs, static threat checks, or cloud heuristics — which are not scalable or secure enough for today’s mobile threat landscape.

Unlike Appdome’s MobileBOT Defense — which provides a dynamic, AI-native approach that evaluates 400+ risk signals inside the app itself — legacy solutions often leave mobile businesses exposed. These older systems typically inspect only a handful of conditions (like emulator or jailbreak status) and rely on insecure architectures that attackers can easily bypass.

As mobile threats become more automated, AI-driven, and fraud-focused, these limitations create gaps that mobile fraudsters exploit. Here are the most common weaknesses holding traditional mobile bot defenses back:

1.  Time-to-Market Delays from SDKs

Anti-bot SDKs often add significant engineering overhead and slow app delivery timelines. Integration disrupts DevOps workflows and release cycles, and the protection provided is typically limited and inflexible.

2.  Insecure Token and Cookie Handling

Many SDKs store cookies, tokens, and session data in plaintext — making them vulnerable to replay attacks. These outdated patterns offer little resistance against modern, automation-driven threats.

3.  Limited Threat Coverage

Legacy solutions typically evaluate only 2–3 indicators (e.g., emulator, root). They fail to detect malware, deepfakes, session hijacks, synthetic users, and other complex mobile attack vectors.

4.  SDK Tampering and Weaponized App Reuse

SDKs that lack runtime protections can be extracted and reused in cloned or malicious apps. Without code obfuscation or tamper-resistance, attackers can bypass protections entirely.

5.  Spoofable Callouts & Misplaced Configurations

Many SDKs rely on spoofable server-side callouts and store sensitive configurations in public parts of the app. This makes it trivial for attackers to inspect, modify, or bypass protections.

6. WAF Lock-In and Infrastructure Inflexibility

Traditional bot solutions often require pairing with a specific WAF. This ties bot protection to infrastructure choices, increasing cost, reducing agility, and complicating enterprise-scale deployments.

7. SDK Conflicts and Developer Overhead

As mobile apps grow more complex, teams often rely on multiple third-party SDKs for fraud prevention, analytics, performance, and user engagement. This stacking of SDKs can lead to integration conflicts, unexpected behaviors, degraded performance, and security gaps. Managing SDK compatibility across platforms and OS versions slows release cycles, increases testing complexity, and drains engineering resources — all while introducing potential downtime or user experience issues in production. 

The Bottom Line:
Mobile threats are evolving rapidly — and web-era SDK models can’t keep up. Appdome’s modern approach eliminates these limitations with runtime enforcement, deep session analysis, flexible WAF integration, and no SDK or server work required.

Appdome MobileBOT Defense – 400+ Dynamic Protections in a Single Anti-Bot Profile

Appdome’s MobileBOT™ Defense is the only solution purpose-built from the ground up to handle the diverse and highly sophisticated chained attacks mobile apps face. It evaluates over 400 attack vectors inside the mobile app environment — across device, OS, app, user interface, and network layers — before any data reaches backend servers. Traditional anti-bot solutions impose major limitations on mobile businesses, forcing them to define protections based on a single domain, URL, or host — an approach that is neither scalable nor practical in today’s mobile environment, where apps interact with multiple APIs and backends simultaneously. MobileBOT™ Defense eliminates this limitation, providing full coverage across every API, URL, and host used by the app.

Key capabilities of Appdome MobileBOT™ Defense:

• In-App Rate Limiting: Controls the flow of API requests at the source, eliminating abusive, malware-controlled, or zombie app behavior without burdening WAF infrastructure. By shifting compute to the mobile app, MobileBOT™ Defense dramatically reduces backend traffic loads and avoids premature WAF upgrades.
• Immutable App Fingerprinting (mTLS Pre-Check): Validates the authenticity of the mobile app itself during the TLS handshake, blocking fake or tampered apps from connecting. Advanced multi-method fingerprinting ensures apps cannot be spoofed, emulated, or cloned, providing an immutable app identity.
• Real-Time Threat Evaluation: Continuously scans for deepfakes, spyware, remote access trojans (RATs), vishing, session hijacking, and more.
• Dynamic API Protection: Allows businesses to tailor protections at the individual API level — applying different risk evaluations for signup, login, payment, or password reset flows.
• Zero-Trust Session Management: Enforces dynamic threat evaluations before allowing connections to critical endpoints.
• Broader and deeper threat coverage: Covers everything from biometric spoofing and session replay to on-device malware and synthetic user behavior.
• Infrastructure efficiency: Reduces WAF and backend infrastructure load by filtering out fake or risky traffic at the edge. Appdome significantly reduces operational costs by keeping bad traffic off the network, avoiding the volumetric model of traditional bot solutions where missed detections increase WAF and bandwidth costs.
• Universal WAF compatibility: Works with any WAF, maximizing existing investments and eliminating the need for costly rip-and-replace projects. Businesses can extend the life and value of their existing WAFs without adding new infrastructure.
• Flexible Enforcement: Configure anti-bot protections at the app level or backend for custom security policies.
• No SDKs, servers, agents, or coding: Full protection is delivered automatically, streamlining app security without impacting release cycles.

This comprehensive, layered defense ensures that only genuine users, on trusted devices, using untampered apps, can connect — dramatically reducing fraud, account takeover risk, and API abuse.

Why AI-Native Defense Is the Only Way Forward

As attackers increasingly leverage AI to automate and personalize mobile fraud, organizations need an equally advanced strategy to fight back. Traditional defenses that rely on static signals, backend heuristics, or fragile SDK integrations can no longer keep pace. Bots today can mimic taps, swipes, and biometrics, evade backend rate limits, and exploit weak API flows—all without ever triggering traditional red flags.

The only effective approach is to embed security directly within the mobile runtime. An AI-native defense model—like Appdome’s—operates inside the app, evaluates over 400 threat signals, and adapts dynamically based on real-time risk. This allows brands to detect, block, and respond to advanced mobile fraud before it ever impacts the backend or user experience.

To future-proof mobile app security against automation, deepfakes, and synthetic fraud, AI-native protection isn’t optional—it’s essential.

Want to learn more about how to protect your mobile business against the next generation of fraud and bot attacks?  Request a demo to see how we do it.