Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Vulnerabilities / Threats

9/14/2020
04:30 PM
Dark Reading
Dark Reading
Products and Releases
50%
50%

Cyber Deception Reduces Data Breach Costs by Over 51% & SOC Inefficiencies by 32%

New report identifies financial savings and increased productivity based on early detection and response efficiency.

FREMONT, Calif.--(BUSINESS WIRE)--Attivo Networks®, an award-winning leader in cyber deception and attacker lateral movement threat detection, today announced the results of a new research report conducted with Kevin Fiscus of Deceptive Defense, Inc., “Cyber Deception Reduces Breach Costs & Increases SOC Efficiency.” The paper identifies the direct and measurable financial and productivity benefits of deception technology for organizations of all types and sizes.

The report reveals that companies utilizing cyber detection reduce data breach-related costs by over 51% as compared to organizations that do not deploy deception technology. The research also indicates that the average reduction in data breach costs is $1.98 million per incident or $75.12 per compromised record. The cost reductions are based on factors of faster detection and response, effective incident response and reduced incident handling complexity.

In addition, it reports that deception technology can significantly reduce time wasted on false positive alerts and increase efficiencies for the typical Security Operations Center (SOC). A recent Ponemon Exabeam SIEM Productivity Study found that the average amount of time spent per SOC analyst per incident was around 10 minutes and SOC analysts waste approximately 26% of their day dealing with false alarms, representing a loss of over $18,000 in productivity per analyst per year. Users of deception technology have cited a 12X time savings when addressing a deception-based alert as opposed to other alerts, which ultimately can save organizations as much as 32% or $22,746 per SOC analyst per year.

"The term 'game changing' is used far too often,” said Kevin Fiscus, SANS Institute Principal Instructor and founder of Deceptive Defense. “Almost as often as so many grand claims are made, they are found to be over-hyped, at best, and for that reason, they are rightly met with suspicion. Cyber deception is different and it’s not just a new iteration of a legacy technology. It literally changes the game of computer security. It changes the rules. It changes the fundamental assumptions that attackers and defenders have relied upon for decades. The true ‘magic’ of cyber deception is that it causes attackers to question everything they believe they know, often stopping an attack before it’s even really started. That is truly game changing."

“Industry research continues to validate why cyber deception is not only a vital control for detection but also one that will yield significant cost savings,” said Carolyn Crandall, Attivo Networks Chief Deception Officer and CMO. “Organizations both large and small are increasingly leveraging deception to create a proactive defense and are adding detection and prevention depth to their security posture. Executives are prioritizing security investments that help them fight disruption of service, prevent ransomware extortion, and ensure the security of their data. The ability to detect attacks early, reduce data breach costs, and improve SOC efficiencies makes cyber deception a critical security control for the enterprise.”

In addition to the financial and productivity benefits provided by deception technology, the report also cites that properly deployed deception technology can reduce a company’s average dwell time between 90% and 97% — down to as little as 5.5 days. This is significant as recent reports show that the current median dwell time is 56 days, and the mean time to identify a breach is 207 days.

This research, when paired with the MITRE ATT&CK® framework DIY APT tool test results, demonstrates how deception technology can be a powerful security control to add to every defender's arsenal. This APT testing specifically validated the Attivo Networks solution’s ability to boost EDR detection rates by an average of 42% and its impact in reducing dwell time.

Unlike other deception solutions, the Attivo ThreatDefend® platform provides comprehensive attack prevention and detection capabilities that enable it to cover not only decoy techniques, but also a wide variety of other methods. The platform proactively diverts attackers away from their targets with fake information that raises an alert and misdirects them to decoys, and through denial of access, can conceal and prevent an attacker from obtaining critical information such as Active Directory objects, data, and file storage systems. With the ability to control the path of the attacker into a decoy, defenders can safely gather the valuable insights that they need to understand their adversary’s tools and techniques, as well as intent.

The “Cyber Deception Reduces Breach Costs & Increases SOC Efficiency” report is available for download here.

About Attivo Networks

Attivo Networks®, the leader in cyber deception and lateral movement attack detection, delivers a superior defense for revealing and preventing unauthorized insider and external threat activity. The customer-proven Attivo ThreatDefend® Platform provides a scalable solution for derailing attackers and reducing the attack surface within user networks, data centers, clouds, remote worksites, and specialized attack surfaces. The portfolio defends at the endpoint, Active Directory, and throughout the network with ground-breaking innovations for preventing and misdirecting lateral attack activity. Forensics, automated attack analysis, and third-party native integrations streamline incident response. The company has won over 130 awards for its technology innovation and leadership. For more information, visit www.attivonetworks.com.

 

Recommended Reading:

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
COVID-19: Latest Security News & Commentary
Dark Reading Staff 9/25/2020
Hacking Yourself: Marie Moe and Pacemaker Security
Gary McGraw Ph.D., Co-founder Berryville Institute of Machine Learning,  9/21/2020
Startup Aims to Map and Track All the IT and Security Things
Kelly Jackson Higgins, Executive Editor at Dark Reading,  9/22/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
Special Report: Computing's New Normal
This special report examines how IT security organizations have adapted to the "new normal" of computing and what the long-term effects will be. Read it and get a unique set of perspectives on issues ranging from new threats & vulnerabilities as a result of remote working to how enterprise security strategy will be affected long term.
Flash Poll
How IT Security Organizations are Attacking the Cybersecurity Problem
How IT Security Organizations are Attacking the Cybersecurity Problem
The COVID-19 pandemic turned the world -- and enterprise computing -- on end. Here's a look at how cybersecurity teams are retrenching their defense strategies, rebuilding their teams, and selecting new technologies to stop the oncoming rise of online attacks.
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-15208
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can ...
CVE-2020-15209
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one....
CVE-2020-15210
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and ...
CVE-2020-15211
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices f...
CVE-2020-15212
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `outpu...