Shield icon showing fraud detection and API security

Beyond Silos: Why Fraud Detection and API Security Must Converge

Fraud detection and cybersecurity have traditionally been separate disciplines. However, increasingly sophisticated attacks, especially those targeting APIs with malicious bots, demand a more integrated defense.

A recent study underscores this urgency, revealing that 57% of organizations cannot reliably detect API-level fraud. As cloud-native apps rely heavily on APIs, they’ve become prime targets. The lines between cybercrime and fraud are dissolving, requiring a strategy that’s both robust and attuned to the unique ways bots exploit business logic flaws.  Prioritizing protection against this type of abuse is crucial for API security, as fraud is a primary motivation for these attacks.

Bots: The enablers of API-centric fraud

Bots have transformed the fraud landscape, and APIs are now their favored playground. The ability of bots to automate tasks, mimic genuine user behavior, and scale operations exponentially poses a unique challenge that legacy security tools struggle to address.

Crucial tactics enabled by bots include:

  • Account Takeover (ATO): Bots test stolen credentials against API endpoints at incredible speeds, attempting to brute-force logins or systematically reset passwords. Successful ATOs expose sensitive data and undermine customer trust.
  • Credential Stuffing: Similar to ATO, but at scale. Bots leverage leaked credential databases, flooding APIs to find valid logins for subsequent exploitation.
  • Fake Account Creation: Bots have an easy mechanism to target APIs designed for account creation, allowing fraudsters to skew metrics, scrape data, or launch spam campaigns en masse.

The move towards a combined framework for API threat detection and business application protection emphasizes proactive, responsive security. This framework addresses a spectrum of risks, especially those posed by automated attacks. Integrating bot detection with application protection is vital. Moreover, since APIs often share identity layers using protocols like OAuth and OIDC, strong security controls at this level bolster defense against both fraud and cyberattacks.

Real-world examples: When bots and API-centric fraud collide

To illustrate the severity of API-centric fraud, let’s consider these examples:

Inventory Manipulation and Scalping: Fraudsters target new or limited-edition product launches, deploying bots to bombard “add to cart” APIs far faster than any human buyer. They may also exploit API logic flaws to manipulate cart quantities. This hoards inventory, preventing legitimate sales, and often results in the items being resold at wildly inflated prices. E-commerce, concert ticketing, and high-demand goods like sneakers or gaming consoles are prime targets, as bulk purchases create lucrative secondary market opportunities for fraudsters.

Loyalty and Reward Program APIs: A Fraudster’s Playground: Loyalty programs heavily dependent on APIs for point management, rewards, and conversions are particularly vulnerable. Attackers can exploit leaked customer credentials to access redemption APIs, enabling them to drain points or use them for unauthorized purchases. They may also target API vulnerabilities, like weak authentication or authorization, to directly manipulate point balances. The goal: Illegitimately obtained points are subsequently redeemed for merchandise or cash equivalents.

Gift Card Balance Abuse: Retailers frequently fall victim to gift card fraud. If APIs that check gift card balances lack robust security (like rate limiting, or requiring authentication), fraudsters can deploy bots to systematically test thousands of possible card numbers. Each successful hit reveals a valid card, which can then be drained through other APIs designed for legitimate purchases. The victim remains unaware of the theft until they try to use their already-depleted gift card.

The path to a converged defense

The shift towards a combined framework for API threat detection and the protection of vital business applications signals a move to proactive and responsive security. These measures aim to tackle a wide range of risks, including those from automated threats.

Here’s what a converged approach entails:

  • Shared Data and Insights: By sharing threat intelligence, security and fraud teams gain a more complete understanding of risks. A spike in login failures could indicate a mere bot attack, but fraud insights might reveal account takeover (ATO) as the true objective.  Robust authentication and authorization controls make it harder to gain initial access to high-value APIs, effectively filtering out bots early in the attack chain.
  • Behavioral Bot Detection: Sophisticated systems go beyond basic traffic patterns, analyzing API interactions and device fingerprinting to unmask bots that closely mimic legitimate users. This data, when correlated with known botnet infrastructure, provides even stronger protection. Since APIs drive business logic for tasks like account creation, referrals, and loyalty point transactions, focusing on anomalies in API sequencing, intervals, call volumes, and source attributes (like IP addresses, potential proxies/VPNs) can yield highly accurate bot detections.
  • Understanding ‘Normal’ API Behavior: Platforms that learn typical API usage patterns can pinpoint subtle deviations. Anomalies like a user adding 1000 items to their cart or a single IP address flooding password reset requests can indicate malicious activity. By responding with fine-grained controls based on device and behavioral fingerprints, businesses can effectively prevent those trying to exploit business logic flaws.

Embracing a holistic strategy enhances the understanding of application abuse patterns, including bot behaviors in critical business functions, enabling more effective threat identification and neutralization.

The bottom line

Companies cannot afford to underestimate the threat bots pose to their API-driven applications and infrastructure. Traditional silos between fraud and security teams create dangerous blind spots. Fraud detection often lacks visibility into API-level attacks, while API security tools may overlook fraudulent behavior disguised as legitimate traffic. This disconnect leaves businesses vulnerable.

By integrating fraud detection, API security, and advanced bot protection, organizations create a more adaptive defense. This proactive approach offers crucial advantages: swift threat response, the ability to anticipate and mitigate vulnerabilities exploited by bots and other malicious techniques, and an in-depth understanding of application abuse patterns. These advantages lead to more effective threat identification and neutralization, combating both low-and-slow attacks and sudden volumetric attacks from bots.

The battle against API-based fraud is ongoing. Businesses that remain complacent risk severe consequences. Proactive collaboration and relentless focus on evolving threats are not optional – they are essential for safeguarding data, customers, and reputations in today’s API-centric world.