Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Artificial Intelligence (AI) is now integrated into almost every available technology. It powers numerous real-world applications, from facial recognition to language translators and virtual assistants. AI offers significant benefits for businesses and economies by boosting productivity and creativity. However, it still faces practical challenges. Machine learning often requires substantial human effort to label training data for supervised learning.

Automatically disrupt attacks and rapidly remediate endpoints.

Bolster your organization’s observability and security capabilities on one platform with AI, anomaly detection, and enhanced attack discovery Organizations in today’s digital landscape are increasingly concerned about service availability and safeguarding their software from malicious tampering and compromise. The traditional security and observability tools often operate in silos, leading to fragmented views and delayed responses to incidents.

As we enter the age of AI, we’ve seen the first wave of AI adoption in software development in the form of coding assistants. Now, we’re seeing the next phase of adoption take place, with organizations leveraging increasingly widely available LLMs to build AI-enabled software. Naturally, as the adoption of LLM platforms like OpenAI and Gemini grows, so does the security risk associated with using them.

Snyk is an excellent tool for spotting project vulnerabilities, including hardcoded secrets. In this blog, we'll show how you can use Snyk to locate hardcoded secrets and credentials and then refactor our code to use Doppler to store those secrets instead. We'll use the open source Snyk goof project as a reference Node.js boilerplate application, so feel free to follow along with us.

Have you ever wanted to fine-tune the configuration of your Bot Management? With self-service rules, you get finer control over bot scoring and customize it according to user behavior on your applications. In this blog, we will cover three use cases that will explain how to use this feature.

Code signing has successfully established itself in the backdrop of the rapidly transforming digital space as a critical security mechanism for software distribution. Through the digital signing of source code, developers and publishers offer users confidence about their software’s validity, founder, and quality. Though cyber threats had been positively enhanced, the demands for a high level of compliance and strict code signing requirements had become more necessary.

A Signed Driver is a software entity which is usually a device driver or can be a kernel module and has been signed cryptographically by its developer or producer using its digital signature. This mark renders a unique identification and authentication mechanism ensuring authorship and integrity protection. Signed drivers are the main actors who guarantee the system’s safety and stability by permitting only trusted and verified software components to communicate with the kernel.

61% of organizations have seen deepfake incidents increase in the past year – with 75% of these attacks impersonating the CEO or another C-suite executive, according to a recent report by Deep Instinct. Moreover, 97% are concerned they will suffer a security incident as a result of adversarial AI.

SQL injection vulnerabilities may affect any website or application that employs an SQL database, such as MySQL, Oracle, SQL Server, or others. Malicious actors may use them to gain unauthorized access to sensitive information, such as customer information, personal data, trade secrets, and more. For example, SQL injections were responsible for 23% of global vulnerabilities in 2023, Moreover, 19% of the internet faces cross-site scripting (stored) attacks.