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.


Securify Pinpoints Insider Threats

New tool tracks end user behavior in real time, helping IT spot potential trouble

"If we'd known what our users were doing, we would have stopped them."

This lament, common among IT security managers, is usually heard after an internal breach. But software vendor Securify Inc. unveiled a tool on Tuesday to help security departments stop unauthorized behavior before it causes serious damage.

The new Securify Appliance line lets IT managers track network and application behavior by user identity in real-time. The products will automatically verify that user behavior on critical business systems complies with security best practices and business controls. The product automatically validates network relationships and behavior against pre-set controls, allowing companies to target where the highest risk behavior is occurring, and then to track it back to an individual user.

The addition of individual identities gives Securify both application-aware and identity-based capabilities to tackle the insider risk problem, says Steve Woo, the vendor's VP of products and marketing. "And Securify continues to automatically validate this granular level of traffic inspection against pre-built controls in real-time, something that application and database activity log analysis can only do way after the fact and typically with cumbersome manual queries," he says.

According to Eric Ogren, analyst at Enterprise Strategy Group, the most common risk of data loss or theft comes from that "the insider risk problem." Insiders include authorized users, but can also be intruders masquerading as credentialed users. "In fact, a Sarbanes-Oxley priority is protecting a firm's financial results against abuse by privileged users, i.e., someone with the power and skills to take data and cover up their tracks," says Ogren. "In some cases, the insider is not being malicious. They simply make security holes while trying to make their job easier. It's not unlike movers who leave a door propped open as they go in and out all day long."

According to Woo, his customers' top concern is gaining visibility into their networks and controlling insider risks, especially from outsourcers and contractors, or from unintentional insecure activity by employees.

Ogren notes that a company's remote offices exacerbate security concerns because those facilities generally have a higher rate of turnover. That means getting remote employees educated and trained on corporate security policies is a challenge.

Securify can be deployed to remote networks, explains Woo. "With network-based monitoring, the solution only needs to be installed on the headquarters's side of the connection to monitor and protect access to the critical business system," he says. Securify can also detect unexpected logins from a remote location indicative of a potential compromise, or flag violations of secure practice if sensitive data is inappropriately accessed while offsite, Woo adds.

Securify 5.2 correlates network activity back to user identities, as well as group association and network location. The Microsoft Active Directory reports user names, machine names, and various application specific logins -- including email, file transfer and others. These activities occur in real-time, so Securify can pinpoint insider misuse, either intentional or unintentional, as it takes place.

"Identity recognition addresses a very important piece of information security that is often overlooked," says Securify user Mike Ma, senior security engineer at Openwave. "Accountability is as important a piece of information security as the traditional concerns around confidentiality, integrity and availability...Securify gives us real time visibility into our network traffic up to the application level. With the new 5.2 release and the identities feature we can now answer the questions of who is doing what, when, and where on our network."

In addition to the tracking benefits, Woo notes that huge cost and time savings are achieved through use of Securify rather than through the traditional manual review of application and database activity logs. "Securify's real-time, continuous verification of all activity versus at most a once a day manual review of a sample of log data also yields true threat protection and operational risk improvement."

Securify is clearly not alone in the network security space, but it's one of the few companies -- if only -- to leverage continuous visibility of users and applications to make intelligent profiles of the business application, touts Ogren. "The advantage is that the competition has trouble being continuous or identifying users so that the monitoring can be more actionable."

For example, network behavior anomaly detection (NBAD) does a great job of continuously monitoring application traffic (destination, source, protocol) but forces IT to manually associate user names with IP addresses. On the other hand, security information management (SIM) does a decent job of collecting log file information, but isn't real-time continuous, Ogren says.

— Jennifer Bosavage, Special to Dark Reading

Companies mentioned in this article:

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
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
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 ...
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....
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 ...
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...
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...