As traditional security measures have strengthened around email and network perimeters, attackers have turned their attention to collaboration platforms. These applications are trusted by users, integrated into business processes, often granted extensive permissions, and frequently bypass traditional security controls.
Digital defenses reports point to attackers exploiting trusted platforms and communication channels to deliver phishing and other identity-based attacks. According to Navigating the Cyber security Landscape: A Comprehensive Review of Cyber-Attacks, Emerging Trends, and Recent Developments by Md Abu Imran Mallick and Rishab Nath, adversaries are now achieving breakout times of just two minutes and seven seconds, showing the need for faster detection and response in cybersecurity.
Despite these threats, organizational preparedness remains inadequate. According to Workplace Collaboration Security Threats are Growing, just 37% of participants said their company had a structured plan for securing their workplace collaboration apps. The World Economic Forum's Global Cybersecurity Outlook 2025 reinforces this concern, revealing that 72% of organizations report increased cyber risks over the past year. This gap between threat and defense leaves organizations exposed.
Furthermore, Mallick and Nath note that the Communications Fraud Control Association reported toll fraud losses had grown to almost $40 billion a year, up 12% from its 2021 survey, as reported by No Jitter. Meanwhile, regulatory enforcement is intensifying—Securities and Exchange Commission fines against companies whose employees used unsupported chat apps for customer communications have exceeded $1 billion.
Several factors make collaboration platforms appealing to threat actors. First, these applications are designed for fast communication and file sharing—the same characteristics that make them productive also make them efficient vehicles for malicious content. Users are conditioned to click links and download files shared by colleagues without the same scrutiny they might apply to external emails.
Secondly, collaboration apps often have extensive integrations and third-party add-ons. Each integration represents a potential entry point. A compromised third-party bot or plugin can provide attackers with access to organizational data and communications. As noted in Transforming Cybersecurity with Agentic AI to Combat Emerging Cyber Threats, unlike traditional systems that function within controlled environments, modern AI agents and integrated tools interact with various systems and external data sources, expanding the potential attack surface.
Thirdly, many organizations have implemented collaboration tools prioritizing functionality and user adoption over security. A cybersecurity advisory from CISA highlights a vulnerability in this approach, noting that many software and hardware products come "out of the box" with overly permissive factory-default configurations intended to make the products user-friendly and reduce troubleshooting time. However, leaving these factory default configurations enabled after installation may provide avenues for attackers to exploit. Default configurations may leave security features disabled, and security teams often lack visibility into activities occurring within these platforms.
The World Economic Forum's research shows another dimension of this problem: only 37% of organizations have processes in place to assess the security of AI tools before deployment. The study further warns that companies may face challenges with "shadow AI," where employees deploy AI tools, such as public AI models for data analysis or AI-powered coding assistants, without proper authorization. An employee may unknowingly input sensitive company data into a public AI tool, leading to potential data breaches.
The No Jitter article notes that the growing deployments of generative AI tools enable rapid creation of content including meeting transcripts, summaries, and action items that may need classification, retention, and protection in accordance with compliance and data loss prevention requirements. Furthermore, generative AI language models may use customer data for analysis and contextual responses, showing the need to ensure that vendors protect customer information.
Protecting against collaboration app-based attacks requires a multi-layered approach that balances security with usability. However, many organizations face a challenge, No Jitter reports that companies are often lacking clear lines of responsibility for workplace collaboration and customer engagement security, with roles frequently split between those responsible for app administration and CISO teams, with no defined approach for establishing and implementing policy, as well as conducting audits.
Organizations must start by establishing governance and accountability structures. Once leadership alignment is achieved, they can implement authentication mechanisms. Implementing multi-factor authentication across all collaboration platforms reduces the risk of account compromise.
Security teams need logging and analytics capabilities to detect suspicious activities within collaboration platforms. The cybersecurity advisory emphasizes that by implementing log collection and retention, organizations are able to have sufficient information to investigate incidents and detect threat actor behavior. This includes monitoring for unusual file sharing patterns, abnormal login locations, excessive permission grants, and communications with external parties. Security solutions can apply machine learning to identify behavior that might indicate a compromised account. For instance, Paubox uses generative AI in its email security platform to detect anomalies in message patterns, flagging suspicious emails that traditional filters might miss.
Access controls and permissions should follow the principle of least privilege. The cybersecurity advisory recommends that organizations give personnel access only to the data, rights, and systems they need to perform their job. Regularly audit who has access to what information and ensure that permissions are appropriately scoped. Limit the ability to share files externally, add third-party integrations, or invite external users to sensitive channels. Implement data loss prevention policies that prevent sensitive information from being shared inappropriately.
The research emphasizes that implementing threat modeling, least-privilege access, and separating trusted from untrusted zones can reduce vulnerabilities. Additionally, monitoring agent activity and maintaining audit trails help detect anomalies effectively. Organizations must also obtain consent for data collection, ensure compliance with sector-specific privacy laws (such as HIPAA), and provide oversight to prevent legal and security risks. According to the World Economic Forum, 54% of large organizations identified supply chain challenges as the biggest barrier to achieving cyber resilience, with 48% of CISOs indicating that ensuring third-party compliance with security requirements is their main challenge.
Employees need to understand the risks associated with collaboration platforms and recognize the signs of potential attacks. Training should cover topics like verifying the identity of message senders, being cautious with unexpected file shares, and reporting suspicious activities.
As recommended in the Transforming Cybersecurity with Agentic AI to Combat Emerging Cyber Threats research, enhancing security awareness through training tools tailored to risk levels is essential. Organizations should also educate employees about social engineering risks and foster a culture of cybersecurity. Mallick and Nath reveal a troubling reality: two out of three organizations report moderate-to-critical skills gaps, with only 14% confident that they have the people and skills needed to meet their cybersecurity requirements. Organizations should foster a security-conscious culture where employees feel empowered to question unusual requests, even when they appear to come from colleagues or supervisors.
Read also: 8 security risks of collaboration tools
AI can monitor user behaviors, file sharing patterns, and access anomalies to flag suspicious activity before attacks escalate.
They can leverage cloud-native security solutions, enforce MFA, restrict third-party integrations, and train staff on phishing awareness.
Vendors must ensure secure default configurations, timely patching, and proper handling of user data to minimize risk exposure.
Automated threat modeling can identify potential vulnerabilities across integrations and workflows, allowing proactive mitigation.
These regulations require data protection, consent management, and access controls to ensure sensitive information shared on collaboration apps is secure.