Secure Execution of Untrusted Code

Secure Execution ofUntrusted Code

Motivation

My Secure PC

UntrustedCode

Mobile code scenarios• Java applet / Javascript in web page

• Postscript / PDF file

• Email attachment

• BPF

• Active networks

• Agent technology

Challenges

Untrusted code may• Read sensitive memory regions

(password, cryptographic keys, db records)• Write memory areas, violate integrity

(overwrite public verification key)• Jump to arbitrary location (jump past password

verification)• Perform arbitrary system calls (execute arbitrary

local programs, access file system)• Waste resources, DoS (memory, computation,

network bandwidth), thrash OS (while 1 do fork())• Crash program, OS

Solution 1: Separate Process

Run untrusted code in separate process Advantages

• Memory separation through VM system Disadvantages

• Inter-Process Communication (IPC) is expensive–Context switch has high overhead (TLB, cache)

• Untrusted code can do any system calls To protect file system, use chroot

Solution 2: Signed Code

Only accept code digitally signed by trusted entity

Advantages• Simple security policy

• Can be secure if trusted entity creates “secure code”

Disadvantages• Security relies on secrecy of private key

• Security relies on authenticity of public key

• Coarse-grained access control

Solution 3: Sandboxing

Run code in limited environment Verify each system call Verify each memory

reference Advantage

• Fine-grained control

Disadvantages• Efficiency• Expressing security policy• Sandbox may have security vulnerabilities

UntrustedCode

Sandbox

Application

Solution 4: SFI

Provide memory safety efficiently• Can only r/w legitimate memory locations

Software fault isolation (SFI): transform untrusted code into safe code• Compiler: generates safe code

–Ship source code, or

–Generate code that verifier can easily check

• Loader (binary patching): rewrite untrusted code

SFI Load each module into its own fault

domain• Code is in read-only part

• Module can r/w anything within fault domain

• Code can only jump within fault domain

Two parts• Efficient Software Encapsulation

• Fast Communication Across Fault Domains

UntrustedCodeApplication Untrusted

CodeUntrusted

Code

Efficient Software Encapsulation

Goal• Only allow writes within data part of fault domain• Only allow jumps within code segment of fault domain

Mechanisms• Split memory space into segments, each segment has a

segment identifier (high-order bits of address), and comprises all addresses for any low-order bits

• Separate code and data segments• Dedicated registers are only used by inserted code, cannot be

modified by untrusted code• Tame unsafe instructions by segment matching or address

sandboxing– PC-relative jumps often safe, static stores are safe– Other stores and jumps are unsafe

RISC Instruction Set Simplifies SFI

Memory accessed with load / store instruction (no add to memory)

All instructions have fixed size, and are aligned• Simplifies instruction verification

• Simplifies jump target verification

Usually large number of registers• Can tolerate giving up 5 dedicated registers

Segment Matching

Verifies correctness of memory accesses Advantage

• Can pinpoint address of offending instruction, useful in debugging

Disadvantage• Slow

dedicated-reg target addressscratch-reg (dedicated-reg >> shift reg)compare scratch-reg and segment-regtrap if not equalstore instruction uses dedicated-reg

Address Sandboxing

Set segment identifier for each memory access / jump instruction• Overwrite segment identifier with fault domain’s

segment identifier

Advantage: efficient Disadvantage: cannot pinpoint flaw, only

enforces that accesses are within domain

dedicated-reg target-reg & and-mask-regdedicated-reg dedicated-reg | segment-regstore instruction uses dedicated-reg

Puzzles

What about the following transformation, not using dedicated register?

target-reg target-reg & and-mask-regtarget-reg target-reg | segment-regstore instruction uses target-reg

What about jumps into SFI verification instructions? Could we jump outside of fault domain? Could we write to code segment? Could we jump to data segment?

What if we only used 4 dedicated registers (sandboxing case, i.e., 1 dedicated-reg for code/data)?

4-Register Attack

jump target-reg

dedicated-reg target-reg & and-mask-regdedicated-reg dedicated-reg | segment-reg-cjump instruction uses dedicated-reg

target-reg = r2

dedicated-reg target-reg & and-mask-regdedicated-reg dedicated-reg | segment-reg-dstore instruction uses dedicated-reg

Verification of Instrumented Code

Problem: given instrumented binary, how can we verify that all rules are met?

Verify that all unsafe stores and jumps use dedicated registers to form address

Verify that all inserted code has correct pattern (identify inserted code by use of dedicated registers)

Fast Communication Across Fault Domains

Use Jump Table with legal entry points outside fault domain

For each call between fault domains, a customized stub procedure is created• Stubs run unprotected outside fault domain• Trusted stub directly copies arguments to

destination domain• Switch execution stack• Set up register context and validate

dedicated registers

SFI Discussion

System calls from fault domain?• Issues and solutions

Allowing arbitrary memory reads? Could we improve the granulartiy of memory

protection?• Missing read protection a problem?

Is granularity of jump protection sufficient? Flexibility for segment size? Internal fragmentation? Can SFI prevent buffer overruns? Is self-modifying code possible? SFI on CISC processors? Can we change compiler once verifier is deployed?

Solution 5: PCC

Proof-carrying code (PCC) developed @ CMU by George Necula and Peter Lee

Goal: safely run code in unsafe languages Approach: create efficiently verifiable proof

that untrusted code satisfies safety policy May not need instrumentation code (no

execution overhead!) if we can prove code safety

Slides based on George Necula’s OSDI96 talk

Proof-Carrying Code: An Analogy

oracle bits

Legend: code proof

Proof-Carrying Code (PCC)

certification

proofvalidation

untrustedapplication code

nativecode

safetyproof

code producer

code consumer

CPU

PCC binary

formalsafety policy

Benefits of PCC

Wide range of safety policiesmemory safety

• resource usage guarantees (CPU, locks, etc.)

• concurrency propertiesdata abstraction boundaries

Wide range of languagesassembly languages

• high-level languages

Simple, fast, easy-to-trust validation Tamper-proof

Experimentation

Goal:• Test feasibility of PCC concept

• Measure costs (proof size and validation time)

Choose simple but practical applicationsNetwork Packet Filters

• IP Checksum

• Extensions to the TIL run-time system for Standard ML

Experimentation (2)

Use DEC Alpha assembly language (hand-optimized for speed)

Network Packet Filters• BPF safety policy: “The packet is read-only

and the scratch memory is read-write. No backward branches. Only aligned memory accesses.”

PCC Implementation (1)

Formalize the safety policy:• Use first-order predicate logic extended with

can_rd(addr) and can_wr(addr)

• Kernel specifies safety preconditions

–Calling convention

–Guaranteed by the kernel to hold on entry

Use tagged memory to define access

i i i i i

j j j j j

.( r mod ) can_rd(r )

.( mod ) can_wr(r )1 0

2

0 8 0

0 16 8 0

PCC Implementation (2)

Compute a safety predicate for the code• Use Floyd-style verification conditions

(VCgen)

• One pass through the code, for example:

–For each LD r,n[rb] add can_rd(rb+n)

–For each ST r,n[rb] add can_wr(rb+n)

Prove the safety predicate• Use a general purpose theorem prover

PCC Implementation (3)

Formal proofs are trees:• the leaves are axiom instances

• the internal nodes are inference rule instances

• at the root is the proved predicate

• Example:

PCC Implementation (4)

Proof Representation: Edinburgh Logical Framework (LF)

Proofs encoded as LF expressions Proof Checking is LF type checking

• simple, fast and easy-to-trust (14 rules)

• 5 pages of C code

• independent of the safety policy or application

• based on well-established results from type-theory and logic

Large design space, not yet explored

Packet Filter Experiments 4 assembly language packet filters (hand-

optimized for speed):1Accepts IP packets (8 instr.)

2Accepts IP packets for 128.2.206 (15 instr.)

3 IP or ARP between 128.2.206 and 128.2.209

4TCP/IP packets for FTP (28 instr.)

Compared with:• Run-Time Checking: Software Fault Isolation

• Safe Language: Modula-3

• Interpretation: Berkeley Packet Filter

Performance Comparison

Off-line packet trace on a DEC Alpha 175MHz PCC packet filters: fastest possible on the architecture The point: Safety without sacrificing performance!

0

0.5

1

1.5

2

2.5

1 2 3 4Filter

Lat

ency

(u

s)

PCC

SFIM3

BPF

Cost of PCC for Packet Filters

Proofs are approx. 3 times larger than the code Validation time: 0.3-1.8ms

Packet Filter 1 2 3 4Instructions 8 15 47 28Proof Size(bytes) 160 225 532 420Validation Time(us) 362 872 1769 1354

Validation Cost (Filter 3)

Conclusion: One-time validation cost amortized quickly

0

3

6

9

12

15

0 10 20 30 40 50

Thousands of packets

ms

PCCSFIM3BPF

PCC for Memory Safety Continuum of choices between static checking and run-time checking:

PCC can be also used where run-time checking cannot (e.g., concurrency)

Run-TimeChecking

StaticChecking

Performance Penalty

Proof ComplexitySFI

What Can We Check With PCC?

Any property with a sound formalization • if you can prove it, PCC can check it!

One proof-checker for many such policies!• Small commitment for open-ended extensibility

Example: policies defined by safe interpreters • E.g, security monitors, memory safety, resource

usage limits, …

… can be enforced statically with PCC• Prove that all run-time checks would succeed• No run-time penalty

PCC Beyond Memory SafetyExample: database with access control

access item price

agent

pricing server

Safety policy:

• host invokes the agent with:

–security clearance level• item and price fields readable

only if access level–parent

• communication permitted only back to parent

• must terminate within MAX instructions

• wait BNDW * SIZE instructions before sending SIZE bytes

• level• parent

PCC is not limited to memory safety!

Practical Difficulties

Proof generation• Similar to program verification

• But:

–done off-line

–can use run-time checks to simplify the proofs

• In restricted cases it is feasible (even automatable)

Proof-size explosion• It is exponential in the worst case

• Not a problem in our experiments

PCC Discussion

A very promising framework for ensuring safety of untrusted code

Limitations? What about generating proof on the fly?

• Could verify safety property based on specific arguments

Related problem: how to secure mobile code from malicious host?