How to Detect Malicious Bots in 2024

As bots, or web robots, have become more sophisticated in 2024, the risk of malicious activity has also increased. Such activity includes using artificial intelligence and other advanced technologies to fly under the radar and carry out attacks at the same time. This might be theft of personal data, account takeover, denial of service, and installing malware. When these bots are able to copy human behavior, they are harder to find, with every bot detected having the potential to cost businesses and individuals billions of dollars. According to Forbes, this includes revenue loss, operational expenses, penalties, and more. Learning how to detect bots is important and Osavul bot monitoring software can help

how to detect bots

Understanding Malicious Bots

The most important way to detect and protect against malicious web robot activity is to understand what they are and how they can get you.

Definition of Malicious Bots

block bot

A malicious bot is software, automated to carry out harmful attacks without a human behind the keyboard or screen. They are very different from the useful bots that carry out tasks on the internet like sorting and customer service. Understanding bot activity and how it operates and what impact they can have is a vital part of any person or entity’s cybersecurity plan.

Common Types of Malicious Bot Activities

In addition to understanding the general definition of web robots, as mentioned above, it’s a good idea to be aware of the types out there, which makes it easier to find a bot when it shows up.

- Web scraping - steal bundles of data without permission, including business details, personal data, and anything covered under privacy policies.
- Credential stuffing - these robots use stolen login information to access accounts.
- Distributed denial of service (DDoS) - a network of infected devices bands together to dramatically and excessively increase traffic, resulting in a shutdown or disrupting a specific service.
- Spamming produces huge floods of unsolicited comments and/or messages to carry out phishing or spread malware to advertise sketchy or non-existent products.
- Click fraud - copy normal user behavior by clicking on ads to increase engagement statistics.
- Social media - create fake social media accounts, which are used to spread fake news and misinformation, skew analytics, and carry out fraud.

Knowing how to spot a bot based on this type of activity can save individuals and businesses money, keep sensitive data safe, and protect the person or organization's reputation. There are a variety of ways to determine if it’s a bot or not. Keep reading to find out what they are.

Bot Detection Techniques

In most cases, figuring out how to detect bots requires a combination of bot detection techniques. Each of the methods described below targets a specific aspect of detection, based on the web robot’s characteristics and activity.

Behavioral Analysis

This technique involves analyzing user behavior on a given platform, network or website to find patterns that point to web robot activity. Not only can this help ensure a bot is detected, but it also assists with identifying evolving robot behavior.
- Interaction patterns - look for actions that are repeated and that are not normal human behaviors.
- Session duration - as compared to humans, a web robot session tends to be excessively long or short.
- Navigation flow - looks at how users engage with a website to find strange sequences or bypass certain steps that point to robot activity.

Machine Learning Algorithms

Machine learning algorithms take on a huge amount of data, which it analyzes as a way to find a bot, based on patterns that don’t look like average human behavior. Supervised - uses labeled data as a way to detect robot behavior.

Unsupervised - without using web robot behavior, this bot detection technique looks for patterns or differences that indicate new activity. Feature extraction - uses features like the IP address, speed of interactions, and more to organize and label traffic.

Signature-Based Detection

This method uses known patterns, often referred to as “signatures” that have been linked to malicious bots. This might be an IP address or malware hashtags.

- Database of signatures - a list of previously known web robot signatures.
- Pattern matching - looks for matches between the signature database and the traffic that is coming in.
- Blacklisting - blocks a bot that is clearly from a known signature.  

Anomaly Detection

Using a baseline of normal activity, this method looks for any straying away from that baseline, which could indicate a bot detected. This is useful for finding new bots or those that have not already been identified.

- Baseline creation - putting together a picture of normal behavior, using historical data.
- Deviation analysis - flags behavior that doesn’t line up with the created baseline.
- Contextual awareness - improves accuracy by taking into account location, time of day, and the role of the user

How to Monitor and Find Bots

Staying on top of your efforts to find a bot is a continuous process that you want to stay on top of. Using a set of proven strategies is a good way to know the difference between an unlikely bot and a malicious web robot that can cause damage. Listed below are some of the primary methods for doing so.

Continuous Network Monitoring

This is the real-time observation of network traffic, allowing for the immediate detection of suspicious activity that could point to a web robot.

- Traffic analysis - monitors the source, the volume, and the destination of all traffic on a given network.
- Protocol monitoring - watches for unauthorized use of protocols, as well as strange behavior when using these protocols.
- Behavior baselines - create a baseline of normal behavior that makes it easier to flag anomalies.

Identifying Bot Messages

By watching automated communications, this method of detection allows for flagging spam, fake social media accounts and/or posts, and automatic chat responses.
- Timing and frequency of messages - look for unnatural frequencies and timing of messages.
- Content analysis - looks through all content, identifying and detecting when automated content is produced in the form of repetition, unnatural language, and specific keywords.
- Source analysis - flags messages that come from suspicious IP addresses or botnets.

Analyze and Identify Accounts that Spread Misinformation and Fake News
A huge number of web robots are used to spread fake news and lies, making it important to find the accounts and analyze the way they are spreading misinformation.
- Behavioral patterns – essentially, analyze human behavior. Look for high activity, repetitive content in posts, and interaction with other suspicious accounts.
- Content verification - makes sure that information shared is from reputable sources and can be backed up to verify authenticity.
- Network analysis - looks at interactions, such as retweets and shares to find accounts that are working together.  

Software Solutions for Bot Detection

The increasing need for individuals and businesses to have the capability to find a bot means that a variety of software continues to evolve to match those needs.

Overview of Bot Detection Software Platforms

Now that you know how to detect bots, it’s time to get the job done. There are several software programs that know how to detect bots. In general, these programs carry out the above-mentioned methods of identifying, flagging, and dealing with web robots. Osavul offers the most cutting-edge technology for the job.

Introduction to Osavul’s Bot Detection and Monitoring Software

This platform is designed to offer dynamic protection against the damaging effects of malicious robot activity. It melds the most advanced technology with a user-friendly design that both detects activity and mitigates threats.

- Real-time detection
- Advanced analytics
- Customizable alert settings
- Integration with existing security systems
- Osavul is the go-to program if you’re looking for diverse protection to help you maintain your security and protect your digital assets, whatever they might be.

Why Choose Osavul’s Bot Detection and Monitoring Software

Knowing how to spot a bot is of utmost importance for fending off coordinated inauthentic behavior, carried out by bots online. That includes spreading fake news and misinformation, changing the narrative, prompting a certain agenda, stealing personal data or digital assets, and much more. Osavul makes this so easy to do with its software features that include:

- Advanced detection capabilities using AI and machine learning
- Comprehensive monitoring tools
- User-friendly interface and easy deployment
- Detailed reporting and analytics
- Customer testimonials and case studies


Knowing and understanding how to find bots is valuable for individuals and businesses and Osavul technology assists when you find a bot and knows exactly what to do when a bot is detected. You can rely on the software’s technology to identify and flag suspicious activity, protecting yourself online, no matter what you’re doing. Combined with your other cybersecurity efforts, anti-bot software can save you time, money, and your reputation without compromising how you do life online.  

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