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.

Perimeter

SAP CSO: Security Requires Context

Security depends on the apps and networks it protects. SAP CSO Justin Somaini discusses three scenarios.

When Justin Somaini talks about security, "context" comes up as often as any technology or process.

"How do we think about security? How do you bring the context of security to the application context?" he asked when Dark Reading interviewed him at the recent Sapphire NOW conference in Orlando, Fla.

Pivoting to an answer, he admitted that the answers are easier for some applications than others. He went on to discuss a trio of context types.

1. Critical Contexts
In an application such as Concur, SAP's travel expense management suite, "there's a lot of travel security in there. There's also fraud protection," Somaini explained. The challenge, he said, is identifying the same sort of contextual framework for other applications, such as those supporting HR or the supply chain.

But doing so is critical. "For us, being able to take security into the line-of-business context is critical," Somiani said. "It's where security really meets the business."

An increased use of analytics is one of the ways Somaini is working to find context. The questions he works through are similar to those many have in data-heavy security: "How much [data] do you need? What are the signals going in that return useful information?" he asked.

The answer is a work in progress. "I believe there's more we can do, but we haven't really figured it out," he admitted.

2. The IoT Context
Talk turned to the Internet of things (IoT). In that context, Somaini said, a particular security difficulty comes with the long reach of the devices at the edge.

"In the IoT, you're including a dependency on the supply chain," he explained. In other words because so many IoT devices are difficult or impossible to upgrade or modify,  to a big extent customers are reliant on the security decisions made by device manufacturers.

In some cases, however, IoT can be easier to secure because the machine-to-machine communications that make up so much of the IoT aren't dependent on the vagaries of user interaction, Somiani said. Yet at the same time, he added, the sheer breadth of the IoT brings its own set of challenges.

"You have to trap the big network that might include cellphones or robots on the factory floor or rail transport," he said. That huge span provides a great deal of room in which criminal activity can hide. For example, a malicious actor from outside of the organization might try to masquerade as someone on the factory floor or as a device on rolling stock.

That possibility means the context has shifted. "Everything we've done previously has been digital, but IoT takes it into the real world," Somaini said.

3. The Employee Context
As the interview neared its end, an SAP employee spotted Somaini and took the opportunity to ask a question about the FBI's recommendation of action on VPNFilter. Somaini answered, and then turned to larger questions about the responsibility of enterprise IT security in the face of such threats.

First, he admitted that it might well be time for CSOs to look at programs to either remediate problems on employees' home routers or show the employees how to remediate issues on their own devices. The issue, he said, is complexity.

"We made the configuration and management of systems incredibly painful. It's impossible for a nonsecurity professional or an end user to set things up," Somaini said.

Somaini also pointed out the similarities between the security challenges of the IoT and those of employees at home. Ultimately, he said, the answer will come in building more security into the systems that machines, enterprise employees, and consumers use to do their work.

Related Content:

 

 

Top industry experts will offer a range of information and insight on who the bad guys are – and why they might be targeting your enterprise. Click for more information

Curtis Franklin Jr. is Senior Editor at Dark Reading. In this role he focuses on product and technology coverage for the publication. In addition he works on audio and video programming for Dark Reading and contributes to activities at Interop ITX, Black Hat, INsecurity, and ... View Full Bio

Comment  | 
Print  | 
More Insights
Comments
Threaded  |  Newest First  |  Oldest First
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...