Three Password Cracking Techniques and How to Defend Against Them - Related to identity:, how, ai, cracking, training

Identity: The New Cybersecurity Battleground

The rapid adoption of cloud services, SaaS applications, and the shift to remote work have fundamentally reshaped how enterprises operate. These technological advances have created a world of opportunity but also brought about complexities that pose significant security threats. At the core of these vulnerabilities lies Identity—the gateway to enterprise security and the number one attack vector for bad actors.

Explore the importance of modernizing Identity strategies and the benefits of centralizing Identity within your security ecosystem to safeguard your organization from costly breaches while enhancing operational efficiency.

Gone are the days when enterprises relied on a single solution tied to a comprehensive license agreement. Businesses today prioritize agility and performance, opting for "best-in-breed" solutions that patch together fragmented tech ecosystems. While these advanced tech stacks provide flexibility, they also create significant challenges for IT and security teams.

Every app, platform, and infrastructure component you add increases the overall complexity of your ecosystem. This fragmentation scatters resources and identities across disconnected silos, limiting visibility and making it easier for cybercriminals to identify and exploit security blind spots. For modern businesses, unmanaged Identity isn't just a weakness—it's the Achilles' heel of enterprise security.

The growing threat of identity-based attacks.

Why is Identity the new prime target? The 2024 Verizon Data Breach analysis found that 80% of breaches involve compromised Identity credentials. With the average time to detect and contain a breach sitting at 290 days, it's clear many organizations are underprepared for these increasingly sophisticated threats. Stunned by the rapid pace of cloud and SaaS adoption, many companies still lack the unified visibility and controls needed to protect their systems and mitigate risks effectively.

Rather than acting as a passive gatekeeper, Identity must now become the foundation of a proactive, defense-first enterprise security strategy.

Centralizing identity within a security ecosystem.

To combat modern threats, enterprises need to rethink their approach to Identity. Centralizing Identity across all systems and applications can significantly reduce security gaps, create real-time insights, and enable faster responses to potential attacks. It's more than just authentication; it's about transforming how organizations utilize Identity as a robust security tool.

Modern, cloud-native Identity solutions empower businesses by delivering three essential capabilities:

Visibility is critical when combating blind spots in fragmented tech stacks. A centralized Identity platform provides unified, real-time insights into your entire ecosystem, helping security teams surface vulnerabilities before they can be exploited. By consolidating all Identity and access data into one platform, enterprises can identify risks faster and prioritize remediation.

Ask yourself, can your Identity solution….

□ Give you visibility into all threats across all systems, devices, and types, and customer accounts?

□ Incorporate third-party signals from across your tech stack (in addition to first-party signals from your Identity provider) for comprehensive, real-time threat visibility?

□ Run automated scans of all your tools and evaluate your setup against an aggregated set of Zero Trust frameworks?

Centralized Identity solutions don't just expose risks—they help eliminate them. Automation enables proactive remediation during potential breaches, from flagging unusual behavior to automatically revoking access. This type of orchestration enhances incident response, making it scalable and efficient even in complex environments.

□ Simplify the task of setting up automated remediation actions?

□ Enable granular customization of remediation actions based on risk factors, policies, and other contextual cues?

□ Trigger robust responses like universal logout to protect against potential breaches?

A modern Identity platform connects seamlessly with your existing tech stack through APIs, unlocking the full value of system-wide security capabilities. Whether it's connecting your cloud services, SaaS applications, or legacy systems, these integrations create a consistent, secure user experience while closing security gaps.

□ Seamlessly integrate with your key enterprise Saas applications, [website], your CRM,.

productivity, collaboration, ERP, and IT ops management apps?

□ Provide deep Identity security capabilities that go beyond simple provisioning and single sign on to provide protection for those apps before, during, and after login?

□ Integrate with core parts of your security stack to enhance risk monitoring, threat detection, and remediation?

Identity-first security creates an open, efficient, and secure ecosystem for managing apps and systems without siloes, custom integrations, or security gaps. The OpenID Foundation's IPSIE working group is working to make this vision a reality.

Your enterprise's success depends on its ability to adapt and thrive in an evolving security landscape. By shifting your mindset and making Identity the foundation of your cybersecurity strategy, your organization can achieve stronger protection, operational efficiencies, and a seamless user experience.

It's time to stop playing defense and start innovating security around Identity. Start with a modern, cloud-based Identity solution that ensures you stay ahead of the threats your systems face daily. Explore how centralizing Identity can transform your security ecosystem today.

[Discover More About Modern Identity Solutions].

Medienberichte über neue Befehle des US-Verteidigungsministers verursachten am Wochenende Aufruhr in der Security-Szene. US-Verteidigungsminister Pete......

Cybersecurity researchers are alerting of an ongoing malicious campaign targeting the Go ecosystem with typosquatted modules that are designed to depl......

Derzeit haben Angreifer Android-Smartphones im Visier und attackieren Geräte. Sicherheitspatches stehen für ausgewählte Geräte bereit. Nach erfolgreic......

Three Password Cracking Techniques and How to Defend Against Them

Passwords are rarely appreciated until a security breach occurs; suffice to say, the importance of a strong password becomes clear only when faced with the consequences of a weak one. However, most end consumers are unaware of just how vulnerable their passwords are to the most common password-cracking methods. The following are the three common techniques for cracking passwords and how to defend against them.

Brute force attacks are straightforward yet highly effective techniques for cracking passwords. These attacks involve malicious actors using automated tools to systematically try every possible password combination through repeated login attempts. While such tools have existed for years, the advent of affordable computing power and storage has made them even more efficient today, especially when weak passwords are used.

When it comes to brute force attacks, malicious actors employ a range of tactics—from simple brute force attacks that test every possible password combination to more nuanced approaches like hybrid and reverse brute force attacks. Each method has a distinct strategy behind it, but the motives behind brute force attacks are the same: to gain unauthorized access to protected data or resources.

Some popular automated tools for carrying out brute force attacks include:

John the Ripper: a multiplatform password cracker with support for 15 different operating systems and hundreds of hashes and cipher types.

L0phtCrack: a tool that uses rainbow tables, dictionaries, and multiprocessor algorithms to crack Windows passwords.

Hashcat: a cracking/password recovery utility that supports five unique modes of attack for over 300 highly-optimized hashing algorithms.

Back in August 2021, [website] mobile operator T-Mobile fell victim to a data breach that started with a brute force attack. The security compromise resulted in the exposure of over 37 million customer records containing sensitive data like social security numbers, driver's license information, and other personally identifiable data.

customers should choose strong, complex passwords and multi-factor authentication (MFA) to protect against brute force attacks. Administrators should implement account lockout policies and continuously audit their Windows environments for weak and breached passwords. Tools like Specops Password Auditor can automate these processes across expansive IT environments.

In a password dictionary attack, cyber attackers try to gain access by using a list of common passwords or words from a dictionary. This predefined word list typically includes the most often used words, phrases, and simple combinations ([website], "admin123"). Password dictionary attacks underscore the importance of complex, unique passwords, as these attack types are especially effective against weak or easily guessable passwords.

The process starts with compiling a list of potential passwords from data breaches, common password lists, or publicly available resources. Using an automated tool, malicious actors perform a dictionary attack, systematically testing each password against a target account or system. If a match is found, the hacker can gain access and carry out subsequent attacks or movements.

Malicious actors used password dictionaries to crack hashed passwords in several high-profile security incidents, such as the 2013 Yahoo data breach and the 2012 LinkedIn data breach. This allowed them to steal the account information of billions of people.

When creating or resetting passwords, customers should use a combination of letters, numbers, and special characters, and avoid using common words or easily guessable phrases. Administrators can implement password complexity requirements in their policies to enforce these mandates across the organization.

A rainbow table attack uses a special table ([website], a "Rainbow Table) made up of precomputed strings or commonly used passwords and corresponding hashes to crack the password hashes in a database.

Rainbow table attacks work by exploiting chains of hashing and reduction operations to efficiently crack hashed passwords. Potential passwords are first hashed and stored alongside their plaintext counterparts in the rainbow table, then processed with a reduction function that maps them to new values, resulting in a chain of hashes. This process is repeated multiple times to build the rainbow table. When hackers obtain a hash list, they can reverse lookup each hash value in the rainbow table—once a match is identified, the corresponding plaintext password is exposed.

While salting (a method of adding random characters to passwords before hashing) has reduced the effectiveness of rainbow table attacks, many hashes remain unsalted; additionally, advances in GPUs and affordable hardware have eliminated the storage limitations once associated with rainbow tables. As a result, these attacks continue to be a likely tactic in current and future high-profile cyber-attacks.

As mentioned previously, salted hashes have significantly reduced the effectiveness of precomputed tables; organizations should therefore implement strong hashing algorithms ([website], bcrypt, scrypt) in their password processes. Administrators should also regularly modification and rotate passwords to reduce the likelihood of rainbow table dictionary matches/hits.

In short, passwords aren't perfect, but complex and sufficiently long passphrases remain a vital first line of defense against advanced password-cracking techniques. Tools like Specops Policy provide an extra layer of protection by continuously scanning Active Directory against a database of over 4 billion breached passwords. Contact us for a free demo today.

The BadBox Android malware botnet has been disrupted again by removing 24 malicious apps from Google Play and sinkholing communications for half a mil......

A [website] Army soldier who pleaded guilty last week to leaking phone records for high-ranking [website] government officials searched online for non-extraditi......

Elastic has rolled out security updates to address a critical security flaw impacting the Kibana data visualization dashboard software for Elasticsear......

The straight and narrow — How to keep ML and AI training on track

Artificial intelligence (AI) and machine learning (ML) have entered the enterprise environment.

, two broad groups are onboarding AI: Leaders and learners. Leaders are seeing quantifiable results, with two-thirds reporting 25% (or greater) boosts to revenue growth. Learners, meanwhile, say they’re following an AI roadmap (72%), but just 40% say their C-suite fully understands the value of AI investment.

One thing they have in common? Challenges with data security. Despite their success with AI and ML, security remains the top concern. Here’s why.

Full steam ahead: How AI and ML get smarter.

Historically, computers did what they were told. Thinking outside the box wasn’t an option — lines of code dictated what was possible and permissible.

AI and ML models take a different approach. Instead of rigid structures, AI and ML models are given general guidelines. Companies supply vast amounts of training data that help these models “learn,” in turn improving their output.

A simple example is an AI tool designed to identify images of dogs. The underlying ML structures provide basic guidance — dogs have four legs, two ears, a tail and fur. Thousands of images of both dogs and not-dogs are provided to AI. The more pictures it “sees,” the improved it becomes at differentiating dogs.

Off the rails: The risks of unauthorized model modification.

If attackers can gain access to AI models, they can modify model outputs. Consider the example above. Malicious actors compromise business networks and flood training models with unlabeled images of cats and images incorrectly labeled as dogs. Over time, model accuracy suffers and outputs are no longer reliable.

Forbes highlights a recent competition that saw hackers trying to “jailbreak” popular AI models and trick them into producing inaccurate or harmful content. The rise of generative tools makes this kind of protection a priority — in 2023, researchers discovered that by simply adding strings of random symbols to the end of queries, they could convince generative AI (gen AI) tools to provide answers that bypassed model safety filters.

And this concern isn’t just conceptual. As noted by The Hacker News, an attack technique known as “Sleepy Pickle” poses significant risks for ML models. By inserting a malicious payload into pickle files — used to serialize Python object structures — attackers can change how models weigh and compare data and alter model outputs. This could allow them to generate misinformation that causes harm to people, steal user data or generate content that contains malicious links.

Staying the course: Three components for advanced security.

To reduce the risk of compromised AI and ML, three components are critical:

Accurate, timely and reliable data underpins usable model outputs. The process of centralizing and correlating this data, however, creates a tempting target for attackers. If they can infiltrate large-scale AI data storage, they can manipulate model outputs.

As a result, enterprises need solutions that automatically and continuously monitor AI infrastructure for signs of compromise.

Changes to AI and ML models can lead to outputs that look legitimate but have been modified by attackers. At best, these outputs inconvenience clients and slow down business processes. At worst, they could negatively impact both reputation and revenue.

To reduce the risk of model manipulation, organizations need tools capable of identifying security vulnerabilities and detecting misconfigurations.

Who’s using models? With what data? And for what purpose? Even if data and models are secured, use by malicious actors may put companies at risk. Continuous compliance monitoring is critical to ensure legitimate use.

AI and ML tools can help enterprises discover data insights and drive increased revenue. If compromised, however, models can be used to deliver inaccurate outputs or deploy malicious code.

With Guardium AI security, businesses are more effective equipped to manage the security risks of sensitive models. See how.

The threat actor known as Dark Caracal has been attributed to a campaign that deployed a remote access trojan called Poco RAT in attacks targeting Spa......

Cyber threats are growing more sophisticated, and traditional security approaches struggle to keep up. Organizations can no longer rely on periodic as......

The FBI joined authorities across Europe last week in seizing domain names for Cracked and Nulled, English-language cybercrime forums with millions of......