In the ever-advancing digital world where every interaction on the web or mobile channel is captured, the prevalence of bad bot attacks continues to advance in a much more rapid pace than ever before. The bad actors continue to deploy advanced & sophisticated bots to carry out attacks to cover multiple different bot threats such as Account Takeover, Denial of Inventory, Form Spamming, Content and Price Scraping, Ad Fraud, etc.
The bot attacks which were very basic in nature till a few years back have now become that much more advanced, sophisticated, and mirroring human behaviour that they are able to challenge and bypass the fortified bot defences that many organizations try to deploy.
The increase in these bot attacks mirror the advancement in technology, the availability of easy access to malicious software, bot automation tools and an easy access to compute resources to run these bot attacks. Also, with the advancement in Generative AI tools, bad actors are able to identify vulnerabilities, generate attack scripts and produce bot attacks that much faster than ever before. With the increasing interconnectedness of the digital ecosystem, the motives behind bot attacks are more malicious and extremely rewarding too if the bad actors manage to succeed in these attacks.
In such a threat landscape, having a robust multi-layered approach towards proactive and effective bot detection and mitigation has become the need of the hour. A simple cookie cutter approach will not be effective and will lead to defence being breached easily.
Limitations of traditional responsive protection against bot attacks
While traditional cookie-cutter approaches to bot detection had worked in the past, they are not capable to compete against the sophistication of modern bot attacks. These legacy methods, reliant on static rules and signatures, are inherently reactive, responding to known threats rather than anticipating emerging risks. Also, relying on indicators such as IP addresses or user-agent strings is no longer sufficient in an era where bots can dynamically change their identities and mimic human behaviour with alarming accuracy. As bots become increasingly adept at masquerading as legitimate users, the efficacy of rule-based detection methods diminishes, leaving organizations vulnerable to exploitation.
Furthermore, the reactive nature of traditional approaches means that the bot attacks get leaked, as bad bots go undetected for long time and by the time a new bot signature is identified and put into the system, the damage is already done.
In light of these challenges, it is evident that a paradigm shift is needed in the approach to bot detection and management. Organizations must embrace a holistic, multi-layered strategy that leverages advanced analytics, machine learning, and proactive threat intelligence to stay ahead of the evolving threat landscape.
Why Radware Bot Manager solution is different and effective?
Radware's Bot Manager solution uses a multi-layered proactive approach to protection to deliver comprehensive application security. This includes Discovery-based Immediate Protection, Pre-emptive Protection, Behavioural-based Detection, and Advanced Mitigation. Now let us dig deeper into each of these layers in more detail.
Discovery-based Immediate Protection: The discover-based Immediate Protection acts like a strong core that leads to the other layers of protection. The whole premise behind this is to have a strong core capability that can through automated traffic discovery enable a very effective “Immediate Protection” that customers get immediately in the onboarding stage itself. This provides a strong base foundation for customers to then get the additional layers of protection that can eventually make the application defence fully unbreachable.
Pre-emptive Protection: This is the first layer of defence that Radware Bot Manager provides. This provides strong and effective protection against bad and rogue IPs and identities. This layer comprises of engines/bot detection modules which can provide robust protection against bots on web, Mobile and API channel thus eliminating lot of “Noise” in the system. This includes our innovative JavaScript Challenge mechanism on the Web that can easily detect and mitigate bots that cannot execute JavaScript. On the mobile channel, this includes our innovative and unique Mobile SDK solution with Attestation support which can easily block all the emulators and requests coming from unrecognized devices and applications. On top of this, this layer includes Radware’s unique AI-based Correlation Engine that can correlate data from multiple products in the portfolio and take a strong, quick, and effective approach to thwart requests coming from unwanted and rouge IPs before they can take a toll on the application infrastructure.
Behavioural-based detection: This is the second layer that focusses on advanced behavioural based detection approach to thwart and mitigate highly sophisticated bot attacks that have become the norm these days. This layer comprises of engines/bot detection modules that utilize AI and intent-based detection algorithms to detect sophisticated distributed attacks, and human-like bots. The advanced behavioural detection modules comprise of the following key ones:
- Rotators: This behavioural detection module can automatically detect both IP and Identity rotation by correlating data across all sub-domains of an application. The module works based on the principle of learning what the peace-time baseline is of IP and Identity rotator and whenever a source makes requests much beyond the peace-time baseline, it is tagged as anomalous.
- Standard and Rare Header Anomaly: These advanced ML-based detection modules work towards identifying anomalies based on HTTP headers. The modules learn what is the expected set of Standard HTTP headers for a major browser version and if we see requests coming either without the standard headers or with rare unseen headers, it flags that source as anomalous.
- CAPTCHA farm detection: This advanced detection module can automatically identify CAPTCHA farms that are deployed to solve the CAPTCHAs based on multiple signals that are tapped into and once a source is detected as using a CAPTCHA farm, that source is unable to access the application even after solving CAPTCHA. This acts as a very strong deterrent against bad bot actors that today have access to resources such as these 3rd party CAPTCHA farm services to solve CAPTCHA and get access to the application.
- Distributed Traffic Anomaly: This is another advanced behavioural detection module detects automatically a highly distributed attack on specific endpoint(s) by seeing the anomaly compared to peace-time traffic that was learnt automatically and once the anomaly is detected, the module is also able to produce the appropriate real-time bot signature pattern to mitigate the attack.
The above list is just a subset of the behavioural detection modules that are part of this second layer of our multi-layered approach.
Advanced Mitigation: This third layer focusses on advanced techniques to mitigate the bot attacks once the detection modules can accurately detect the bad bot attacks. Once the bad bots are identified, you need to be able to effectively stop them from accessing the applications. This is where Radware Bot Manager offers advanced mitigation techniques which include a host of mitigation options that also has the unique and differentiating CAPTCHA-less Crypto Challenge mitigation. Our unique strong differentiator in this layer is also our proprietary real-time signature creation module that can (irrespective of which detection module is at play) be able to automatically identify the common bot pattern signature in the attack and push this signature in real-time to mitigate the attack. This ensures that both False Positives (FPs) and False Negatives (FNs) are kept to the bare minimum because of the accuracy of the signature.
To Summarize:
Radware Bot Manager with its innovative and holistic multi-layered strategy that leverages advanced machine learning and robust behavioural detection capabilities continues to stay ahead of the evolving threat landscape. We continue to evolve and add additional capabilities that make the Radware Bot Manager solution the best-in-class in the bot management landscape.
Contact us to learn more about proactive application protection strategies and AI-based solutions.